Overview

Brought to you by YData

Dataset statistics

Number of variables223
Number of observations724508
Missing cells121397885
Missing cells (%)75.1%
Total size in memory1.2 GiB
Average record size in memory1.7 KiB

Variable types

Numeric20
Unsupported116
Text83
Boolean4

Dataset

DescriptionNMNH Paleobiology Specimen Records (USNM) 0049391-241126133413365
URLhttps://doi.org/10.15468/dl.ws2uf3

Alerts

license has constant value "CC0_1_0" Constant
publisher has constant value "National Museum of Natural History, Smithsonian Institution" Constant
institutionID has constant value "http://biocol.org/urn:lsid:biocol.org:col:34871" Constant
collectionID has constant value "urn:uuid:ce595e88-ceba-42c0-a3ff-cd55b694fac" Constant
institutionCode has constant value "USNM" Constant
collectionCode has constant value "PAL" Constant
datasetName has constant value "NMNH Paleobiology (USNM)" Constant
basisOfRecord has constant value "FOSSIL_SPECIMEN" Constant
occurrenceStatus has constant value "PRESENT" Constant
verbatimCoordinateSystem has constant value "Degrees Minutes Seconds" Constant
datasetKey has constant value "c8681cc2-9d0a-4c5f-b620-5c753abfe2bc" Constant
publishingCountry has constant value "US" Constant
typifiedName has constant value "Type" Constant
protocol has constant value "EML" Constant
lastCrawled has constant value "2024-12-02T10:02:33.848Z" Constant
isSequenced has constant value "False" Constant
publishedByGbifRegion has constant value "NORTH_AMERICA" Constant
hasGeospatialIssues is highly imbalanced (98.1%) Imbalance
accessRights has 724508 (100.0%) missing values Missing
bibliographicCitation has 724508 (100.0%) missing values Missing
language has 724508 (100.0%) missing values Missing
references has 724508 (100.0%) missing values Missing
rightsHolder has 724508 (100.0%) missing values Missing
type has 724508 (100.0%) missing values Missing
datasetID has 724508 (100.0%) missing values Missing
ownerInstitutionCode has 724508 (100.0%) missing values Missing
informationWithheld has 724508 (100.0%) missing values Missing
dataGeneralizations has 724508 (100.0%) missing values Missing
dynamicProperties has 724508 (100.0%) missing values Missing
catalogNumber has 50535 (7.0%) missing values Missing
recordNumber has 675939 (93.3%) missing values Missing
recordedBy has 563497 (77.8%) missing values Missing
recordedByID has 724508 (100.0%) missing values Missing
organismQuantity has 724508 (100.0%) missing values Missing
organismQuantityType has 724508 (100.0%) missing values Missing
sex has 724508 (100.0%) missing values Missing
lifeStage has 724508 (100.0%) missing values Missing
reproductiveCondition has 724508 (100.0%) missing values Missing
caste has 724508 (100.0%) missing values Missing
behavior has 724508 (100.0%) missing values Missing
vitality has 724508 (100.0%) missing values Missing
establishmentMeans has 724508 (100.0%) missing values Missing
degreeOfEstablishment has 724508 (100.0%) missing values Missing
pathway has 724508 (100.0%) missing values Missing
georeferenceVerificationStatus has 724508 (100.0%) missing values Missing
preparations has 591600 (81.7%) missing values Missing
disposition has 724508 (100.0%) missing values Missing
associatedOccurrences has 724508 (100.0%) missing values Missing
associatedReferences has 724508 (100.0%) missing values Missing
associatedSequences has 724508 (100.0%) missing values Missing
associatedTaxa has 724508 (100.0%) missing values Missing
otherCatalogNumbers has 724508 (100.0%) missing values Missing
occurrenceRemarks has 638259 (88.1%) missing values Missing
organismID has 724508 (100.0%) missing values Missing
organismName has 724508 (100.0%) missing values Missing
organismScope has 724508 (100.0%) missing values Missing
associatedOrganisms has 724508 (100.0%) missing values Missing
previousIdentifications has 724508 (100.0%) missing values Missing
organismRemarks has 724508 (100.0%) missing values Missing
materialEntityID has 724508 (100.0%) missing values Missing
materialEntityRemarks has 724508 (100.0%) missing values Missing
verbatimLabel has 724508 (100.0%) missing values Missing
materialSampleID has 724508 (100.0%) missing values Missing
eventID has 724508 (100.0%) missing values Missing
parentEventID has 724508 (100.0%) missing values Missing
eventType has 724508 (100.0%) missing values Missing
fieldNumber has 720044 (99.4%) missing values Missing
eventDate has 474561 (65.5%) missing values Missing
eventTime has 724508 (100.0%) missing values Missing
startDayOfYear has 593923 (82.0%) missing values Missing
endDayOfYear has 593923 (82.0%) missing values Missing
year has 474684 (65.5%) missing values Missing
month has 572740 (79.1%) missing values Missing
day has 596444 (82.3%) missing values Missing
verbatimEventDate has 445814 (61.5%) missing values Missing
habitat has 724508 (100.0%) missing values Missing
samplingProtocol has 724508 (100.0%) missing values Missing
sampleSizeValue has 724508 (100.0%) missing values Missing
sampleSizeUnit has 724508 (100.0%) missing values Missing
samplingEffort has 724508 (100.0%) missing values Missing
fieldNotes has 724508 (100.0%) missing values Missing
eventRemarks has 724508 (100.0%) missing values Missing
locationID has 335037 (46.2%) missing values Missing
higherGeographyID has 724508 (100.0%) missing values Missing
higherGeography has 148417 (20.5%) missing values Missing
continent has 195168 (26.9%) missing values Missing
waterBody has 696851 (96.2%) missing values Missing
islandGroup has 723710 (99.9%) missing values Missing
island has 714401 (98.6%) missing values Missing
countryCode has 158422 (21.9%) missing values Missing
stateProvince has 226462 (31.3%) missing values Missing
county has 454433 (62.7%) missing values Missing
municipality has 724508 (100.0%) missing values Missing
locality has 560871 (77.4%) missing values Missing
verbatimLocality has 724508 (100.0%) missing values Missing
verbatimElevation has 724311 (> 99.9%) missing values Missing
verticalDatum has 724508 (100.0%) missing values Missing
verbatimDepth has 724424 (> 99.9%) missing values Missing
minimumDistanceAboveSurfaceInMeters has 724508 (100.0%) missing values Missing
maximumDistanceAboveSurfaceInMeters has 724508 (100.0%) missing values Missing
locationAccordingTo has 724508 (100.0%) missing values Missing
locationRemarks has 724508 (100.0%) missing values Missing
decimalLatitude has 620570 (85.7%) missing values Missing
decimalLongitude has 620570 (85.7%) missing values Missing
coordinateUncertaintyInMeters has 724508 (100.0%) missing values Missing
coordinatePrecision has 724508 (100.0%) missing values Missing
pointRadiusSpatialFit has 724508 (100.0%) missing values Missing
verbatimCoordinateSystem has 654265 (90.3%) missing values Missing
verbatimSRS has 724508 (100.0%) missing values Missing
footprintWKT has 724508 (100.0%) missing values Missing
footprintSRS has 724508 (100.0%) missing values Missing
footprintSpatialFit has 724508 (100.0%) missing values Missing
georeferencedBy has 724508 (100.0%) missing values Missing
georeferencedDate has 724508 (100.0%) missing values Missing
georeferenceProtocol has 695012 (95.9%) missing values Missing
georeferenceSources has 724508 (100.0%) missing values Missing
georeferenceRemarks has 724503 (> 99.9%) missing values Missing
geologicalContextID has 724508 (100.0%) missing values Missing
earliestEonOrLowestEonothem has 724508 (100.0%) missing values Missing
latestEonOrHighestEonothem has 724508 (100.0%) missing values Missing
earliestEraOrLowestErathem has 220036 (30.4%) missing values Missing
latestEraOrHighestErathem has 718163 (99.1%) missing values Missing
earliestPeriodOrLowestSystem has 245750 (33.9%) missing values Missing
latestPeriodOrHighestSystem has 718167 (99.1%) missing values Missing
earliestEpochOrLowestSeries has 376914 (52.0%) missing values Missing
latestEpochOrHighestSeries has 718290 (99.1%) missing values Missing
earliestAgeOrLowestStage has 562472 (77.6%) missing values Missing
latestAgeOrHighestStage has 722133 (99.7%) missing values Missing
lowestBiostratigraphicZone has 724508 (100.0%) missing values Missing
highestBiostratigraphicZone has 724508 (100.0%) missing values Missing
lithostratigraphicTerms has 724508 (100.0%) missing values Missing
group has 633218 (87.4%) missing values Missing
formation has 365706 (50.5%) missing values Missing
member has 643191 (88.8%) missing values Missing
bed has 724508 (100.0%) missing values Missing
identificationID has 724508 (100.0%) missing values Missing
verbatimIdentification has 724508 (100.0%) missing values Missing
identificationQualifier has 724508 (100.0%) missing values Missing
typeStatus has 582086 (80.3%) missing values Missing
identifiedBy has 521981 (72.0%) missing values Missing
identifiedByID has 724508 (100.0%) missing values Missing
dateIdentified has 724508 (100.0%) missing values Missing
identificationReferences has 724508 (100.0%) missing values Missing
identificationVerificationStatus has 724508 (100.0%) missing values Missing
identificationRemarks has 724508 (100.0%) missing values Missing
taxonID has 724508 (100.0%) missing values Missing
scientificNameID has 724508 (100.0%) missing values Missing
acceptedNameUsageID has 171789 (23.7%) missing values Missing
parentNameUsageID has 724508 (100.0%) missing values Missing
originalNameUsageID has 724508 (100.0%) missing values Missing
nameAccordingToID has 724508 (100.0%) missing values Missing
namePublishedInID has 724508 (100.0%) missing values Missing
taxonConceptID has 724508 (100.0%) missing values Missing
acceptedNameUsage has 724508 (100.0%) missing values Missing
parentNameUsage has 724508 (100.0%) missing values Missing
originalNameUsage has 724508 (100.0%) missing values Missing
nameAccordingTo has 724508 (100.0%) missing values Missing
namePublishedIn has 724508 (100.0%) missing values Missing
namePublishedInYear has 724508 (100.0%) missing values Missing
higherClassification has 172643 (23.8%) missing values Missing
phylum has 192842 (26.6%) missing values Missing
class has 272566 (37.6%) missing values Missing
order has 369296 (51.0%) missing values Missing
superfamily has 724508 (100.0%) missing values Missing
family has 258765 (35.7%) missing values Missing
subfamily has 724508 (100.0%) missing values Missing
tribe has 724508 (100.0%) missing values Missing
subtribe has 724508 (100.0%) missing values Missing
genus has 245070 (33.8%) missing values Missing
genericName has 244897 (33.8%) missing values Missing
subgenus has 724508 (100.0%) missing values Missing
infragenericEpithet has 724508 (100.0%) missing values Missing
specificEpithet has 449718 (62.1%) missing values Missing
infraspecificEpithet has 718207 (99.1%) missing values Missing
cultivarEpithet has 724508 (100.0%) missing values Missing
verbatimTaxonRank has 724508 (100.0%) missing values Missing
vernacularName has 724508 (100.0%) missing values Missing
nomenclaturalCode has 724508 (100.0%) missing values Missing
taxonomicStatus has 171789 (23.7%) missing values Missing
nomenclaturalStatus has 724508 (100.0%) missing values Missing
taxonRemarks has 724508 (100.0%) missing values Missing
elevation has 724508 (100.0%) missing values Missing
elevationAccuracy has 724508 (100.0%) missing values Missing
depth has 724508 (100.0%) missing values Missing
depthAccuracy has 724508 (100.0%) missing values Missing
distanceFromCentroidInMeters has 723864 (99.9%) missing values Missing
mediaType has 637882 (88.0%) missing values Missing
acceptedTaxonKey has 171789 (23.7%) missing values Missing
phylumKey has 192842 (26.6%) missing values Missing
classKey has 272566 (37.6%) missing values Missing
orderKey has 369296 (51.0%) missing values Missing
familyKey has 258765 (35.7%) missing values Missing
genusKey has 245070 (33.8%) missing values Missing
subgenusKey has 724508 (100.0%) missing values Missing
speciesKey has 450165 (62.1%) missing values Missing
species has 450165 (62.1%) missing values Missing
acceptedScientificName has 171789 (23.7%) missing values Missing
verbatimScientificName has 171332 (23.6%) missing values Missing
typifiedName has 724501 (> 99.9%) missing values Missing
repatriated has 158317 (21.9%) missing values Missing
relativeOrganismQuantity has 724508 (100.0%) missing values Missing
projectId has 724508 (100.0%) missing values Missing
gbifRegion has 160612 (22.2%) missing values Missing
level0Gid has 686240 (94.7%) missing values Missing
level0Name has 686240 (94.7%) missing values Missing
level1Gid has 686243 (94.7%) missing values Missing
level1Name has 686243 (94.7%) missing values Missing
level2Gid has 687320 (94.9%) missing values Missing
level2Name has 687320 (94.9%) missing values Missing
level3Gid has 722506 (99.7%) missing values Missing
level3Name has 722506 (99.7%) missing values Missing
iucnRedListCategory has 365809 (50.5%) missing values Missing
individualCount is highly skewed (γ1 = 32.66226483) Skewed
gbifID has unique values Unique
occurrenceID has unique values Unique
accessRights is an unsupported type, check if it needs cleaning or further analysis Unsupported
bibliographicCitation is an unsupported type, check if it needs cleaning or further analysis Unsupported
language is an unsupported type, check if it needs cleaning or further analysis Unsupported
references is an unsupported type, check if it needs cleaning or further analysis Unsupported
rightsHolder is an unsupported type, check if it needs cleaning or further analysis Unsupported
type is an unsupported type, check if it needs cleaning or further analysis Unsupported
datasetID is an unsupported type, check if it needs cleaning or further analysis Unsupported
ownerInstitutionCode is an unsupported type, check if it needs cleaning or further analysis Unsupported
informationWithheld is an unsupported type, check if it needs cleaning or further analysis Unsupported
dataGeneralizations is an unsupported type, check if it needs cleaning or further analysis Unsupported
dynamicProperties is an unsupported type, check if it needs cleaning or further analysis Unsupported
recordedByID is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismQuantity is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismQuantityType is an unsupported type, check if it needs cleaning or further analysis Unsupported
sex is an unsupported type, check if it needs cleaning or further analysis Unsupported
lifeStage is an unsupported type, check if it needs cleaning or further analysis Unsupported
reproductiveCondition is an unsupported type, check if it needs cleaning or further analysis Unsupported
caste is an unsupported type, check if it needs cleaning or further analysis Unsupported
behavior is an unsupported type, check if it needs cleaning or further analysis Unsupported
vitality is an unsupported type, check if it needs cleaning or further analysis Unsupported
establishmentMeans is an unsupported type, check if it needs cleaning or further analysis Unsupported
degreeOfEstablishment is an unsupported type, check if it needs cleaning or further analysis Unsupported
pathway is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferenceVerificationStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
disposition is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedOccurrences is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedReferences is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedSequences is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedTaxa is an unsupported type, check if it needs cleaning or further analysis Unsupported
otherCatalogNumbers is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismID is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismName is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismScope is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedOrganisms is an unsupported type, check if it needs cleaning or further analysis Unsupported
previousIdentifications is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialEntityID is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialEntityRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimLabel is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialSampleID is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventID is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentEventID is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventType is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventTime is an unsupported type, check if it needs cleaning or further analysis Unsupported
habitat is an unsupported type, check if it needs cleaning or further analysis Unsupported
samplingProtocol is an unsupported type, check if it needs cleaning or further analysis Unsupported
sampleSizeValue is an unsupported type, check if it needs cleaning or further analysis Unsupported
sampleSizeUnit is an unsupported type, check if it needs cleaning or further analysis Unsupported
samplingEffort is an unsupported type, check if it needs cleaning or further analysis Unsupported
fieldNotes is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
higherGeographyID is an unsupported type, check if it needs cleaning or further analysis Unsupported
municipality is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimLocality is an unsupported type, check if it needs cleaning or further analysis Unsupported
verticalDatum is an unsupported type, check if it needs cleaning or further analysis Unsupported
minimumDistanceAboveSurfaceInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
maximumDistanceAboveSurfaceInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationAccordingTo is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
coordinateUncertaintyInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
coordinatePrecision is an unsupported type, check if it needs cleaning or further analysis Unsupported
pointRadiusSpatialFit is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimSRS is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintWKT is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintSRS is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintSpatialFit is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferencedBy is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferencedDate is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferenceSources is an unsupported type, check if it needs cleaning or further analysis Unsupported
geologicalContextID is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestEonOrLowestEonothem is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestEonOrHighestEonothem is an unsupported type, check if it needs cleaning or further analysis Unsupported
lowestBiostratigraphicZone is an unsupported type, check if it needs cleaning or further analysis Unsupported
highestBiostratigraphicZone is an unsupported type, check if it needs cleaning or further analysis Unsupported
lithostratigraphicTerms is an unsupported type, check if it needs cleaning or further analysis Unsupported
bed is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationID is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimIdentification is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationQualifier is an unsupported type, check if it needs cleaning or further analysis Unsupported
identifiedByID is an unsupported type, check if it needs cleaning or further analysis Unsupported
dateIdentified is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationReferences is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationVerificationStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonID is an unsupported type, check if it needs cleaning or further analysis Unsupported
scientificNameID is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentNameUsageID is an unsupported type, check if it needs cleaning or further analysis Unsupported
originalNameUsageID is an unsupported type, check if it needs cleaning or further analysis Unsupported
nameAccordingToID is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedInID is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonConceptID is an unsupported type, check if it needs cleaning or further analysis Unsupported
acceptedNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
originalNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
nameAccordingTo is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedIn is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedInYear is an unsupported type, check if it needs cleaning or further analysis Unsupported
superfamily is an unsupported type, check if it needs cleaning or further analysis Unsupported
subfamily is an unsupported type, check if it needs cleaning or further analysis Unsupported
tribe is an unsupported type, check if it needs cleaning or further analysis Unsupported
subtribe is an unsupported type, check if it needs cleaning or further analysis Unsupported
subgenus is an unsupported type, check if it needs cleaning or further analysis Unsupported
infragenericEpithet is an unsupported type, check if it needs cleaning or further analysis Unsupported
cultivarEpithet is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimTaxonRank is an unsupported type, check if it needs cleaning or further analysis Unsupported
vernacularName is an unsupported type, check if it needs cleaning or further analysis Unsupported
nomenclaturalCode is an unsupported type, check if it needs cleaning or further analysis Unsupported
nomenclaturalStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
elevation is an unsupported type, check if it needs cleaning or further analysis Unsupported
elevationAccuracy is an unsupported type, check if it needs cleaning or further analysis Unsupported
depth is an unsupported type, check if it needs cleaning or further analysis Unsupported
depthAccuracy is an unsupported type, check if it needs cleaning or further analysis Unsupported
subgenusKey is an unsupported type, check if it needs cleaning or further analysis Unsupported
relativeOrganismQuantity is an unsupported type, check if it needs cleaning or further analysis Unsupported
projectId is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonKey has 171789 (23.7%) zeros Zeros
kingdomKey has 171929 (23.7%) zeros Zeros

Reproduction

Analysis started2025-01-07 16:05:10.892081
Analysis finished2025-01-07 16:05:35.148459
Duration24.26 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

gbifID
Real number (ℝ)

Unique 

Distinct724508
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1489761894
Minimum1316557246
Maximum4987259380
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:35.363140image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1316557246
5-th percentile1316593481
Q11316738419
median1316919584
Q31317100741
95-th percentile3311023845
Maximum4987259380
Range3670702134
Interquartile range (IQR)362322.5

Descriptive statistics

Standard deviation567530383.1
Coefficient of variation (CV)0.3809537521
Kurtosis11.81732068
Mean1489761894
Median Absolute Deviation (MAD)181161.5
Skewness3.474773969
Sum1.07934441 × 1015
Variance3.220907357 × 1017
MonotonicityNot monotonic
2025-01-07T11:05:35.431179image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1317202435 1
 
< 0.1%
1316557253 1
 
< 0.1%
2235727162 1
 
< 0.1%
1316557263 1
 
< 0.1%
1316557258 1
 
< 0.1%
1316557269 1
 
< 0.1%
1316557294 1
 
< 0.1%
3311036301 1
 
< 0.1%
1316557274 1
 
< 0.1%
1316557307 1
 
< 0.1%
Other values (724498) 724498
> 99.9%
ValueCountFrequency (%)
1316557246 1
< 0.1%
1316557247 1
< 0.1%
1316557248 1
< 0.1%
1316557249 1
< 0.1%
1316557250 1
< 0.1%
ValueCountFrequency (%)
4987259380 1
< 0.1%
4987259379 1
< 0.1%
4987259378 1
< 0.1%
4987259377 1
< 0.1%
4987259376 1
< 0.1%

accessRights
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

bibliographicCitation
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

language
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

license
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:35.476181image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters5071556
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCC0_1_0
2nd rowCC0_1_0
3rd rowCC0_1_0
4th rowCC0_1_0
5th rowCC0_1_0
ValueCountFrequency (%)
cc0_1_0 724508
100.0%
2025-01-07T11:05:35.668118image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1449016
28.6%
0 1449016
28.6%
_ 1449016
28.6%
1 724508
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5071556
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1449016
28.6%
0 1449016
28.6%
_ 1449016
28.6%
1 724508
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5071556
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1449016
28.6%
0 1449016
28.6%
_ 1449016
28.6%
1 724508
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5071556
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1449016
28.6%
0 1449016
28.6%
_ 1449016
28.6%
1 724508
14.3%
Distinct6008
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:35.782496image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters14490160
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1783 ?
Unique (%)0.2%

Sample

1st row2014-11-25T18:32:00Z
2nd row2024-10-17T09:58:00Z
3rd row2024-10-17T10:44:00Z
4th row2024-08-03T21:41:00Z
5th row2024-10-17T10:17:00Z
ValueCountFrequency (%)
2024-08-03t22:06:00z 11077
 
1.5%
2024-08-03t22:09:00z 9194
 
1.3%
2024-08-03t22:08:00z 6946
 
1.0%
2024-11-18t11:29:00z 6500
 
0.9%
2024-11-18t11:28:00z 6488
 
0.9%
2024-10-17t10:55:00z 6364
 
0.9%
2024-10-17t10:57:00z 6355
 
0.9%
2024-10-17t10:29:00z 6348
 
0.9%
2024-10-17t10:28:00z 6344
 
0.9%
2024-10-17t10:56:00z 6343
 
0.9%
Other values (5998) 652549
90.1%
2025-01-07T11:05:35.963295image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3567224
24.6%
1 2229486
15.4%
2 1840704
12.7%
- 1449016
10.0%
: 1449016
10.0%
4 856419
 
5.9%
Z 724508
 
5.0%
T 724508
 
5.0%
7 523431
 
3.6%
3 323301
 
2.2%
Other values (4) 802547
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14490160
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 3567224
24.6%
1 2229486
15.4%
2 1840704
12.7%
- 1449016
10.0%
: 1449016
10.0%
4 856419
 
5.9%
Z 724508
 
5.0%
T 724508
 
5.0%
7 523431
 
3.6%
3 323301
 
2.2%
Other values (4) 802547
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14490160
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 3567224
24.6%
1 2229486
15.4%
2 1840704
12.7%
- 1449016
10.0%
: 1449016
10.0%
4 856419
 
5.9%
Z 724508
 
5.0%
T 724508
 
5.0%
7 523431
 
3.6%
3 323301
 
2.2%
Other values (4) 802547
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14490160
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 3567224
24.6%
1 2229486
15.4%
2 1840704
12.7%
- 1449016
10.0%
: 1449016
10.0%
4 856419
 
5.9%
Z 724508
 
5.0%
T 724508
 
5.0%
7 523431
 
3.6%
3 323301
 
2.2%
Other values (4) 802547
 
5.5%

publisher
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:36.036639image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length59
Median length59
Mean length59
Min length59

Characters and Unicode

Total characters42745972
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNational Museum of Natural History, Smithsonian Institution
2nd rowNational Museum of Natural History, Smithsonian Institution
3rd rowNational Museum of Natural History, Smithsonian Institution
4th rowNational Museum of Natural History, Smithsonian Institution
5th rowNational Museum of Natural History, Smithsonian Institution
ValueCountFrequency (%)
national 724508
14.3%
museum 724508
14.3%
of 724508
14.3%
natural 724508
14.3%
history 724508
14.3%
smithsonian 724508
14.3%
institution 724508
14.3%
2025-01-07T11:05:36.146914image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 5071556
11.9%
i 4347048
10.2%
4347048
10.2%
o 3622540
 
8.5%
a 3622540
 
8.5%
n 3622540
 
8.5%
s 2898032
 
6.8%
u 2898032
 
6.8%
N 1449016
 
3.4%
m 1449016
 
3.4%
Other values (11) 9418604
22.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 42745972
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 5071556
11.9%
i 4347048
10.2%
4347048
10.2%
o 3622540
 
8.5%
a 3622540
 
8.5%
n 3622540
 
8.5%
s 2898032
 
6.8%
u 2898032
 
6.8%
N 1449016
 
3.4%
m 1449016
 
3.4%
Other values (11) 9418604
22.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 42745972
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 5071556
11.9%
i 4347048
10.2%
4347048
10.2%
o 3622540
 
8.5%
a 3622540
 
8.5%
n 3622540
 
8.5%
s 2898032
 
6.8%
u 2898032
 
6.8%
N 1449016
 
3.4%
m 1449016
 
3.4%
Other values (11) 9418604
22.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 42745972
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 5071556
11.9%
i 4347048
10.2%
4347048
10.2%
o 3622540
 
8.5%
a 3622540
 
8.5%
n 3622540
 
8.5%
s 2898032
 
6.8%
u 2898032
 
6.8%
N 1449016
 
3.4%
m 1449016
 
3.4%
Other values (11) 9418604
22.0%

references
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

rightsHolder
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

type
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:36.205506image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length47
Median length47
Mean length47
Min length47

Characters and Unicode

Total characters34051876
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttp://biocol.org/urn:lsid:biocol.org:col:34871
2nd rowhttp://biocol.org/urn:lsid:biocol.org:col:34871
3rd rowhttp://biocol.org/urn:lsid:biocol.org:col:34871
4th rowhttp://biocol.org/urn:lsid:biocol.org:col:34871
5th rowhttp://biocol.org/urn:lsid:biocol.org:col:34871
ValueCountFrequency (%)
http://biocol.org/urn:lsid:biocol.org:col:34871 724508
100.0%
2025-01-07T11:05:36.318176image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 5071556
14.9%
: 3622540
 
10.6%
l 2898032
 
8.5%
i 2173524
 
6.4%
c 2173524
 
6.4%
/ 2173524
 
6.4%
r 2173524
 
6.4%
. 1449016
 
4.3%
t 1449016
 
4.3%
b 1449016
 
4.3%
Other values (12) 9418604
27.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 34051876
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 5071556
14.9%
: 3622540
 
10.6%
l 2898032
 
8.5%
i 2173524
 
6.4%
c 2173524
 
6.4%
/ 2173524
 
6.4%
r 2173524
 
6.4%
. 1449016
 
4.3%
t 1449016
 
4.3%
b 1449016
 
4.3%
Other values (12) 9418604
27.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 34051876
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 5071556
14.9%
: 3622540
 
10.6%
l 2898032
 
8.5%
i 2173524
 
6.4%
c 2173524
 
6.4%
/ 2173524
 
6.4%
r 2173524
 
6.4%
. 1449016
 
4.3%
t 1449016
 
4.3%
b 1449016
 
4.3%
Other values (12) 9418604
27.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 34051876
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 5071556
14.9%
: 3622540
 
10.6%
l 2898032
 
8.5%
i 2173524
 
6.4%
c 2173524
 
6.4%
/ 2173524
 
6.4%
r 2173524
 
6.4%
. 1449016
 
4.3%
t 1449016
 
4.3%
b 1449016
 
4.3%
Other values (12) 9418604
27.7%

collectionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:36.376179image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length44
Median length44
Mean length44
Min length44

Characters and Unicode

Total characters31878352
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:ce595e88-ceba-42c0-a3ff-cd55b694fac
2nd rowurn:uuid:ce595e88-ceba-42c0-a3ff-cd55b694fac
3rd rowurn:uuid:ce595e88-ceba-42c0-a3ff-cd55b694fac
4th rowurn:uuid:ce595e88-ceba-42c0-a3ff-cd55b694fac
5th rowurn:uuid:ce595e88-ceba-42c0-a3ff-cd55b694fac
ValueCountFrequency (%)
urn:uuid:ce595e88-ceba-42c0-a3ff-cd55b694fac 724508
100.0%
2025-01-07T11:05:36.482749image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 3622540
 
11.4%
5 2898032
 
9.1%
- 2898032
 
9.1%
u 2173524
 
6.8%
f 2173524
 
6.8%
a 2173524
 
6.8%
e 2173524
 
6.8%
: 1449016
 
4.5%
4 1449016
 
4.5%
8 1449016
 
4.5%
Other values (10) 9418604
29.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 31878352
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 3622540
 
11.4%
5 2898032
 
9.1%
- 2898032
 
9.1%
u 2173524
 
6.8%
f 2173524
 
6.8%
a 2173524
 
6.8%
e 2173524
 
6.8%
: 1449016
 
4.5%
4 1449016
 
4.5%
8 1449016
 
4.5%
Other values (10) 9418604
29.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 31878352
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 3622540
 
11.4%
5 2898032
 
9.1%
- 2898032
 
9.1%
u 2173524
 
6.8%
f 2173524
 
6.8%
a 2173524
 
6.8%
e 2173524
 
6.8%
: 1449016
 
4.5%
4 1449016
 
4.5%
8 1449016
 
4.5%
Other values (10) 9418604
29.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 31878352
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 3622540
 
11.4%
5 2898032
 
9.1%
- 2898032
 
9.1%
u 2173524
 
6.8%
f 2173524
 
6.8%
a 2173524
 
6.8%
e 2173524
 
6.8%
: 1449016
 
4.5%
4 1449016
 
4.5%
8 1449016
 
4.5%
Other values (10) 9418604
29.5%

datasetID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

institutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:36.524262image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2898032
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSNM
2nd rowUSNM
3rd rowUSNM
4th rowUSNM
5th rowUSNM
ValueCountFrequency (%)
usnm 724508
100.0%
2025-01-07T11:05:36.617003image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 724508
25.0%
S 724508
25.0%
N 724508
25.0%
M 724508
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2898032
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 724508
25.0%
S 724508
25.0%
N 724508
25.0%
M 724508
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2898032
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 724508
25.0%
S 724508
25.0%
N 724508
25.0%
M 724508
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2898032
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 724508
25.0%
S 724508
25.0%
N 724508
25.0%
M 724508
25.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:36.658003image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters2173524
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPAL
2nd rowPAL
3rd rowPAL
4th rowPAL
5th rowPAL
ValueCountFrequency (%)
pal 724508
100.0%
2025-01-07T11:05:36.754150image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 724508
33.3%
A 724508
33.3%
L 724508
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2173524
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
P 724508
33.3%
A 724508
33.3%
L 724508
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2173524
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
P 724508
33.3%
A 724508
33.3%
L 724508
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2173524
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
P 724508
33.3%
A 724508
33.3%
L 724508
33.3%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:36.800384image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters17388192
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Paleobiology (USNM)
2nd rowNMNH Paleobiology (USNM)
3rd rowNMNH Paleobiology (USNM)
4th rowNMNH Paleobiology (USNM)
5th rowNMNH Paleobiology (USNM)
ValueCountFrequency (%)
nmnh 724508
33.3%
paleobiology 724508
33.3%
usnm 724508
33.3%
2025-01-07T11:05:36.904552image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 2173524
12.5%
o 2173524
12.5%
M 1449016
 
8.3%
l 1449016
 
8.3%
1449016
 
8.3%
P 724508
 
4.2%
H 724508
 
4.2%
a 724508
 
4.2%
e 724508
 
4.2%
b 724508
 
4.2%
Other values (7) 5071556
29.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17388192
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 2173524
12.5%
o 2173524
12.5%
M 1449016
 
8.3%
l 1449016
 
8.3%
1449016
 
8.3%
P 724508
 
4.2%
H 724508
 
4.2%
a 724508
 
4.2%
e 724508
 
4.2%
b 724508
 
4.2%
Other values (7) 5071556
29.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17388192
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 2173524
12.5%
o 2173524
12.5%
M 1449016
 
8.3%
l 1449016
 
8.3%
1449016
 
8.3%
P 724508
 
4.2%
H 724508
 
4.2%
a 724508
 
4.2%
e 724508
 
4.2%
b 724508
 
4.2%
Other values (7) 5071556
29.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17388192
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 2173524
12.5%
o 2173524
12.5%
M 1449016
 
8.3%
l 1449016
 
8.3%
1449016
 
8.3%
P 724508
 
4.2%
H 724508
 
4.2%
a 724508
 
4.2%
e 724508
 
4.2%
b 724508
 
4.2%
Other values (7) 5071556
29.2%

ownerInstitutionCode
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

basisOfRecord
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:36.952549image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters10867620
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFOSSIL_SPECIMEN
2nd rowFOSSIL_SPECIMEN
3rd rowFOSSIL_SPECIMEN
4th rowFOSSIL_SPECIMEN
5th rowFOSSIL_SPECIMEN
ValueCountFrequency (%)
fossil_specimen 724508
100.0%
2025-01-07T11:05:37.055985image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 2173524
20.0%
E 1449016
13.3%
I 1449016
13.3%
O 724508
 
6.7%
F 724508
 
6.7%
_ 724508
 
6.7%
L 724508
 
6.7%
P 724508
 
6.7%
C 724508
 
6.7%
M 724508
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10867620
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 2173524
20.0%
E 1449016
13.3%
I 1449016
13.3%
O 724508
 
6.7%
F 724508
 
6.7%
_ 724508
 
6.7%
L 724508
 
6.7%
P 724508
 
6.7%
C 724508
 
6.7%
M 724508
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10867620
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 2173524
20.0%
E 1449016
13.3%
I 1449016
13.3%
O 724508
 
6.7%
F 724508
 
6.7%
_ 724508
 
6.7%
L 724508
 
6.7%
P 724508
 
6.7%
C 724508
 
6.7%
M 724508
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10867620
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 2173524
20.0%
E 1449016
13.3%
I 1449016
13.3%
O 724508
 
6.7%
F 724508
 
6.7%
_ 724508
 
6.7%
L 724508
 
6.7%
P 724508
 
6.7%
C 724508
 
6.7%
M 724508
 
6.7%

informationWithheld
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

dataGeneralizations
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

dynamicProperties
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

occurrenceID
Text

Unique 

Distinct724508
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:37.460954image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters45644004
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique724508 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/300009e1e-4f3e-4240-b198-9ea1352b28b5
2nd rowhttp://n2t.net/ark:/65665/30000a59d-34e5-42b6-837d-ad1b89b6b930
3rd rowhttp://n2t.net/ark:/65665/3000109b9-b6d6-4ca0-8f0c-ddde53458300
4th rowhttp://n2t.net/ark:/65665/30001bcd8-61d5-492a-ad56-f8131f24bdaa
5th rowhttp://n2t.net/ark:/65665/300020a6b-970f-4e44-adb4-6d605be80b0d
ValueCountFrequency (%)
http://n2t.net/ark:/65665/3000b8435-5842-4aec-9f71-ae67fb3f2d11 1
 
< 0.1%
http://n2t.net/ark:/65665/3fffd826a-5e86-4d74-a844-8f977557540e 1
 
< 0.1%
http://n2t.net/ark:/65665/300009e1e-4f3e-4240-b198-9ea1352b28b5 1
 
< 0.1%
http://n2t.net/ark:/65665/30000a59d-34e5-42b6-837d-ad1b89b6b930 1
 
< 0.1%
http://n2t.net/ark:/65665/3000109b9-b6d6-4ca0-8f0c-ddde53458300 1
 
< 0.1%
http://n2t.net/ark:/65665/30001bcd8-61d5-492a-ad56-f8131f24bdaa 1
 
< 0.1%
http://n2t.net/ark:/65665/300020a6b-970f-4e44-adb4-6d605be80b0d 1
 
< 0.1%
http://n2t.net/ark:/65665/300045523-2307-4a34-b888-fb51510870ad 1
 
< 0.1%
http://n2t.net/ark:/65665/300045db2-681e-481a-836e-3643bf3debbf 1
 
< 0.1%
http://n2t.net/ark:/65665/300051080-c843-47ad-99d7-ee3ab98a03ba 1
 
< 0.1%
Other values (724498) 724498
> 99.9%
2025-01-07T11:05:37.926169image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 3622540
 
7.9%
6 3531516
 
7.7%
- 2898032
 
6.3%
t 2898032
 
6.3%
5 2808306
 
6.2%
a 2263386
 
5.0%
e 2084462
 
4.6%
2 2083197
 
4.6%
3 2083153
 
4.6%
4 2081137
 
4.6%
Other values (16) 19290243
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 45644004
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 3622540
 
7.9%
6 3531516
 
7.7%
- 2898032
 
6.3%
t 2898032
 
6.3%
5 2808306
 
6.2%
a 2263386
 
5.0%
e 2084462
 
4.6%
2 2083197
 
4.6%
3 2083153
 
4.6%
4 2081137
 
4.6%
Other values (16) 19290243
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 45644004
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 3622540
 
7.9%
6 3531516
 
7.7%
- 2898032
 
6.3%
t 2898032
 
6.3%
5 2808306
 
6.2%
a 2263386
 
5.0%
e 2084462
 
4.6%
2 2083197
 
4.6%
3 2083153
 
4.6%
4 2081137
 
4.6%
Other values (16) 19290243
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 45644004
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 3622540
 
7.9%
6 3531516
 
7.7%
- 2898032
 
6.3%
t 2898032
 
6.3%
5 2808306
 
6.2%
a 2263386
 
5.0%
e 2084462
 
4.6%
2 2083197
 
4.6%
3 2083153
 
4.6%
4 2081137
 
4.6%
Other values (16) 19290243
42.3%

catalogNumber
Text

Missing 

Distinct655081
Distinct (%)97.2%
Missing50535
Missing (%)7.0%
Memory size5.5 MiB
2025-01-07T11:05:38.398581image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length14
Mean length13.86868317
Min length7

Characters and Unicode

Total characters9347118
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique638257 ?
Unique (%)94.7%

Sample

1st rowUSNM SD38013 0000
2nd rowUSNM PAL706968
3rd rowUSNM PAL248638
4th rowUSNM PAL456768
5th rowUSNM PAL297724
ValueCountFrequency (%)
usnm 673973
47.8%
0000 59177
 
4.2%
0001 159
 
< 0.1%
0002 159
 
< 0.1%
0003 149
 
< 0.1%
0004 145
 
< 0.1%
0005 137
 
< 0.1%
0006 116
 
< 0.1%
0007 113
 
< 0.1%
0008 105
 
< 0.1%
Other values (652937) 674632
47.9%
2025-01-07T11:05:38.922158image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 742844
 
7.9%
734892
 
7.9%
M 712585
 
7.6%
N 674519
 
7.2%
U 674214
 
7.2%
0 557394
 
6.0%
P 521957
 
5.6%
A 511374
 
5.5%
L 497601
 
5.3%
1 444334
 
4.8%
Other values (58) 3275404
35.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9347118
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 742844
 
7.9%
734892
 
7.9%
M 712585
 
7.6%
N 674519
 
7.2%
U 674214
 
7.2%
0 557394
 
6.0%
P 521957
 
5.6%
A 511374
 
5.5%
L 497601
 
5.3%
1 444334
 
4.8%
Other values (58) 3275404
35.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9347118
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 742844
 
7.9%
734892
 
7.9%
M 712585
 
7.6%
N 674519
 
7.2%
U 674214
 
7.2%
0 557394
 
6.0%
P 521957
 
5.6%
A 511374
 
5.5%
L 497601
 
5.3%
1 444334
 
4.8%
Other values (58) 3275404
35.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9347118
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 742844
 
7.9%
734892
 
7.9%
M 712585
 
7.6%
N 674519
 
7.2%
U 674214
 
7.2%
0 557394
 
6.0%
P 521957
 
5.6%
A 511374
 
5.5%
L 497601
 
5.3%
1 444334
 
4.8%
Other values (58) 3275404
35.0%

recordNumber
Text

Missing 

Distinct39872
Distinct (%)82.1%
Missing675939
Missing (%)93.3%
Memory size5.5 MiB
2025-01-07T11:05:39.119643image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length48
Median length5
Mean length6.205336737
Min length1

Characters and Unicode

Total characters301387
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37721 ?
Unique (%)77.7%

Sample

1st rowPALMER LOC 1479
2nd row75432
3rd rowH-11
4th rowE73-59
5th rowGaxin Loc 178-36
ValueCountFrequency (%)
loc 1685
 
2.9%
emlong 951
 
1.7%
urbac 803
 
1.4%
olson 263
 
0.5%
sample 209
 
0.4%
hass 177
 
0.3%
rb 171
 
0.3%
c-29 169
 
0.3%
gibson 163
 
0.3%
wyo 162
 
0.3%
Other values (38506) 52476
91.7%
2025-01-07T11:05:39.460645image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 30021
 
10.0%
5 27939
 
9.3%
7 23690
 
7.9%
2 21570
 
7.2%
3 20657
 
6.9%
6 18998
 
6.3%
8 18791
 
6.2%
0 17388
 
5.8%
4 17006
 
5.6%
- 16559
 
5.5%
Other values (67) 88768
29.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 301387
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 30021
 
10.0%
5 27939
 
9.3%
7 23690
 
7.9%
2 21570
 
7.2%
3 20657
 
6.9%
6 18998
 
6.3%
8 18791
 
6.2%
0 17388
 
5.8%
4 17006
 
5.6%
- 16559
 
5.5%
Other values (67) 88768
29.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 301387
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 30021
 
10.0%
5 27939
 
9.3%
7 23690
 
7.9%
2 21570
 
7.2%
3 20657
 
6.9%
6 18998
 
6.3%
8 18791
 
6.2%
0 17388
 
5.8%
4 17006
 
5.6%
- 16559
 
5.5%
Other values (67) 88768
29.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 301387
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 30021
 
10.0%
5 27939
 
9.3%
7 23690
 
7.9%
2 21570
 
7.2%
3 20657
 
6.9%
6 18998
 
6.3%
8 18791
 
6.2%
0 17388
 
5.8%
4 17006
 
5.6%
- 16559
 
5.5%
Other values (67) 88768
29.5%

recordedBy
Text

Missing 

Distinct3957
Distinct (%)2.5%
Missing563497
Missing (%)77.8%
Memory size5.5 MiB
2025-01-07T11:05:39.672010image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length119
Median length61
Mean length10.93147052
Min length1

Characters and Unicode

Total characters1760087
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1329 ?
Unique (%)0.8%

Sample

1st rowR. Snow
2nd rowD. Palmer
3rd rowW. Woodring & L. Lupher
4th rowJames
5th rowRoss
ValueCountFrequency (%)
21228
 
6.1%
j 19727
 
5.7%
r 15376
 
4.5%
w 14249
 
4.1%
a 12060
 
3.5%
james 11468
 
3.3%
l 10757
 
3.1%
woodring 9356
 
2.7%
pribyl 8943
 
2.6%
c 7362
 
2.1%
Other values (2560) 214833
62.2%
2025-01-07T11:05:39.960289image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
184348
 
10.5%
e 133592
 
7.6%
. 131492
 
7.5%
r 102132
 
5.8%
o 91217
 
5.2%
l 89319
 
5.1%
n 89079
 
5.1%
a 84651
 
4.8%
i 80231
 
4.6%
s 70452
 
4.0%
Other values (51) 703574
40.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1760087
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
184348
 
10.5%
e 133592
 
7.6%
. 131492
 
7.5%
r 102132
 
5.8%
o 91217
 
5.2%
l 89319
 
5.1%
n 89079
 
5.1%
a 84651
 
4.8%
i 80231
 
4.6%
s 70452
 
4.0%
Other values (51) 703574
40.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1760087
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
184348
 
10.5%
e 133592
 
7.6%
. 131492
 
7.5%
r 102132
 
5.8%
o 91217
 
5.2%
l 89319
 
5.1%
n 89079
 
5.1%
a 84651
 
4.8%
i 80231
 
4.6%
s 70452
 
4.0%
Other values (51) 703574
40.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1760087
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
184348
 
10.5%
e 133592
 
7.6%
. 131492
 
7.5%
r 102132
 
5.8%
o 91217
 
5.2%
l 89319
 
5.1%
n 89079
 
5.1%
a 84651
 
4.8%
i 80231
 
4.6%
s 70452
 
4.0%
Other values (51) 703574
40.0%

recordedByID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

individualCount
Real number (ℝ)

Skewed 

Distinct686
Distinct (%)0.1%
Missing303
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean11.84197706
Minimum0
Maximum15000
Zeros158
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:40.048766image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile16
Maximum15000
Range15000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation133.8531974
Coefficient of variation (CV)11.30328126
Kurtosis1553.85833
Mean11.84197706
Median Absolute Deviation (MAD)0
Skewness32.66226483
Sum8576019
Variance17916.67846
MonotonicityNot monotonic
2025-01-07T11:05:40.117540image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 594864
82.1%
2 29629
 
4.1%
3 14673
 
2.0%
4 9858
 
1.4%
5 7420
 
1.0%
6 5780
 
0.8%
7 4510
 
0.6%
8 3695
 
0.5%
10 3151
 
0.4%
9 3129
 
0.4%
Other values (676) 47496
 
6.6%
ValueCountFrequency (%)
0 158
 
< 0.1%
1 594864
82.1%
2 29629
 
4.1%
3 14673
 
2.0%
4 9858
 
1.4%
ValueCountFrequency (%)
15000 1
 
< 0.1%
9999 2
 
< 0.1%
9942 1
 
< 0.1%
9000 8
< 0.1%
8000 5
< 0.1%

organismQuantity
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

organismQuantityType
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

sex
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

lifeStage
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

reproductiveCondition
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

caste
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

behavior
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

vitality
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

establishmentMeans
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

degreeOfEstablishment
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

pathway
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

georeferenceVerificationStatus
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

occurrenceStatus
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:40.157542image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters5071556
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPRESENT
2nd rowPRESENT
3rd rowPRESENT
4th rowPRESENT
5th rowPRESENT
ValueCountFrequency (%)
present 724508
100.0%
2025-01-07T11:05:40.253487image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 1449016
28.6%
P 724508
14.3%
R 724508
14.3%
S 724508
14.3%
N 724508
14.3%
T 724508
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5071556
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 1449016
28.6%
P 724508
14.3%
R 724508
14.3%
S 724508
14.3%
N 724508
14.3%
T 724508
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5071556
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 1449016
28.6%
P 724508
14.3%
R 724508
14.3%
S 724508
14.3%
N 724508
14.3%
T 724508
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5071556
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 1449016
28.6%
P 724508
14.3%
R 724508
14.3%
S 724508
14.3%
N 724508
14.3%
T 724508
14.3%

preparations
Text

Missing 

Distinct381
Distinct (%)0.3%
Missing591600
Missing (%)81.7%
Memory size5.5 MiB
2025-01-07T11:05:40.332483image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length94
Median length91
Mean length16.14684594
Min length3

Characters and Unicode

Total characters2146045
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)0.1%

Sample

1st rowBoxes and vials
2nd rowThin sections
3rd rowSecondary microslides
4th rowWet
5th rowplastic container
ValueCountFrequency (%)
microslide 45697
17.5%
microslides 34837
13.4%
secondary 33230
12.8%
remnants 26629
10.2%
thin 24547
9.4%
sections 24011
9.2%
no 15071
 
5.8%
with 10919
 
4.2%
unsectioned 9109
 
3.5%
bottle 3934
 
1.5%
Other values (53) 32636
12.5%
2025-01-07T11:05:40.478237image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 236706
11.0%
s 211809
9.9%
e 210870
9.8%
n 172401
 
8.0%
o 167894
 
7.8%
c 147453
 
6.9%
r 146905
 
6.8%
d 130804
 
6.1%
127712
 
6.0%
l 92477
 
4.3%
Other values (41) 501014
23.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2146045
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 236706
11.0%
s 211809
9.9%
e 210870
9.8%
n 172401
 
8.0%
o 167894
 
7.8%
c 147453
 
6.9%
r 146905
 
6.8%
d 130804
 
6.1%
127712
 
6.0%
l 92477
 
4.3%
Other values (41) 501014
23.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2146045
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 236706
11.0%
s 211809
9.9%
e 210870
9.8%
n 172401
 
8.0%
o 167894
 
7.8%
c 147453
 
6.9%
r 146905
 
6.8%
d 130804
 
6.1%
127712
 
6.0%
l 92477
 
4.3%
Other values (41) 501014
23.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2146045
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 236706
11.0%
s 211809
9.9%
e 210870
9.8%
n 172401
 
8.0%
o 167894
 
7.8%
c 147453
 
6.9%
r 146905
 
6.8%
d 130804
 
6.1%
127712
 
6.0%
l 92477
 
4.3%
Other values (41) 501014
23.3%

disposition
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

associatedOccurrences
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

associatedReferences
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

associatedSequences
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

associatedTaxa
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

otherCatalogNumbers
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

occurrenceRemarks
Text

Missing 

Distinct38195
Distinct (%)44.3%
Missing638259
Missing (%)88.1%
Memory size5.5 MiB
2025-01-07T11:05:40.691172image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1257
Median length1240
Mean length357.4557966
Min length5

Characters and Unicode

Total characters30830205
Distinct characters92
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36384 ?
Unique (%)42.2%

Sample

1st rowSpecimen comments: Associated w/ #0343 and #0346. | Body size code: medium; Taphonomic Significance: Human modification | Features: Weathering, diagenesis: N/A; Burn Color: none; Burn Modification: none; Cut: 0; Scrape: 0; Chop: 0; Loading Notch: 0; Counterblow: 0; Anvil pit: 0; Carn pit: 0; Carn score: 0; Carn furrow: 0; Carn punct: 0; Carn crenulation: 0; Rodent gnaw: none
2nd rowEMu record was created as part of the Smithsonian Institution Digitization Program Office (SI DPO) mass digitization pilot project to support the National Science Foundation Advancing Digitization of Biodiversity Collections Eastern Pacific Invertebrates of the Cenozoic Collaborative Thematic Collections Network (NSF ADBC EPICC TCN). The SI DPO mass digitization pilot workflow includes crowdsourced label transcription through the SI Transcription Center.; Information generated by NMNH Department of Paleobiology volunteers: Specimen count and preliminary identification to class.
3rd rowEMu record was created as part of the Smithsonian Institution Digitization Program Office (SI DPO) mass digitization pilot project to support the National Science Foundation Advancing Digitization of Biodiversity Collections Eastern Pacific Invertebrates of the Cenozoic Collaborative Thematic Collections Network (NSF ADBC EPICC TCN). The SI DPO mass digitization pilot workflow includes crowdsourced label transcription through the SI Transcription Center.; Information generated by NMNH Department of Paleobiology volunteers: Specimen count and preliminary identification to class.
4th rowThe fossil is marked with the original Green River number and is often mistaken for the USNM number. That original Green River collection number is 75432.; Numbers associated with this fossil: 578683. 75432. 40193.
5th rowEMu record was created as part of the Smithsonian Institution Digitization Program Office (SI DPO) mass digitization pilot project to support the National Science Foundation Advancing Digitization of Biodiversity Collections Eastern Pacific Invertebrates of the Cenozoic Collaborative Thematic Collections Network (NSF ADBC EPICC TCN). The SI DPO mass digitization pilot workflow includes crowdsourced label transcription through the SI Transcription Center.; Additional label information: This locality is at approximately the same horizon as USGS CENO LOC 5686, in which a shale fauna was collected | See USGS CENO LOC 5703; Verbatim Lithostratigraphy: Tejon Formation; Sandstone forming the upper member of the Tejon | Discontinuous lenses in a soft brownish sandstone, less than 100 feet stratigraphically below the overlying diatomaceous shale; Verbatim Chronostratigraphy: Eocene
ValueCountFrequency (%)
the 291111
 
6.9%
digitization 174338
 
4.1%
of 164357
 
3.9%
si 100203
 
2.4%
collections 99405
 
2.4%
number 86263
 
2.0%
is 85833
 
2.0%
mass 74949
 
1.8%
dpo 74947
 
1.8%
with 57325
 
1.4%
Other values (66970) 3009589
71.3%
2025-01-07T11:05:40.977677image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4132071
 
13.4%
i 2608470
 
8.5%
t 2311910
 
7.5%
o 2139574
 
6.9%
e 2129723
 
6.9%
n 1708168
 
5.5%
a 1671073
 
5.4%
r 1554155
 
5.0%
s 1249854
 
4.1%
c 981043
 
3.2%
Other values (82) 10344164
33.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 30830205
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4132071
 
13.4%
i 2608470
 
8.5%
t 2311910
 
7.5%
o 2139574
 
6.9%
e 2129723
 
6.9%
n 1708168
 
5.5%
a 1671073
 
5.4%
r 1554155
 
5.0%
s 1249854
 
4.1%
c 981043
 
3.2%
Other values (82) 10344164
33.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 30830205
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4132071
 
13.4%
i 2608470
 
8.5%
t 2311910
 
7.5%
o 2139574
 
6.9%
e 2129723
 
6.9%
n 1708168
 
5.5%
a 1671073
 
5.4%
r 1554155
 
5.0%
s 1249854
 
4.1%
c 981043
 
3.2%
Other values (82) 10344164
33.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 30830205
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4132071
 
13.4%
i 2608470
 
8.5%
t 2311910
 
7.5%
o 2139574
 
6.9%
e 2129723
 
6.9%
n 1708168
 
5.5%
a 1671073
 
5.4%
r 1554155
 
5.0%
s 1249854
 
4.1%
c 981043
 
3.2%
Other values (82) 10344164
33.6%

organismID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

organismName
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

organismScope
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

associatedOrganisms
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

previousIdentifications
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

organismRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

materialEntityID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

materialEntityRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

verbatimLabel
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

materialSampleID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

eventID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

parentEventID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

eventType
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

fieldNumber
Text

Missing 

Distinct1516
Distinct (%)34.0%
Missing720044
Missing (%)99.4%
Memory size5.5 MiB
2025-01-07T11:05:41.176471image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length209
Median length45
Mean length35.25537634
Min length1

Characters and Unicode

Total characters157380
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1229 ?
Unique (%)27.5%

Sample

1st rowMTC-08009; MTC-08009B; MTC-08009B (A); MTC-08009B (B)
2nd row217
3rd rowYP79-2
4th rowTDP31
5th row82-10; 82-19; 82-21; 82-22; 82-4; 82-6; 82-7
ValueCountFrequency (%)
82-19 767
 
4.2%
82-4 767
 
4.2%
82-7 767
 
4.2%
82-10 767
 
4.2%
82-21 767
 
4.2%
82-22 767
 
4.2%
82-6 767
 
4.2%
mtc-04028ee 329
 
1.8%
mtc-04028d 329
 
1.8%
mtc-04028cc 329
 
1.8%
Other values (1502) 11759
64.9%
2025-01-07T11:05:41.421823image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18832
12.0%
- 15944
10.1%
2 14513
9.2%
13651
 
8.7%
; 12694
 
8.1%
8 11928
 
7.6%
C 9870
 
6.3%
M 9201
 
5.8%
T 8674
 
5.5%
4 7381
 
4.7%
Other values (62) 34692
22.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 157380
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 18832
12.0%
- 15944
10.1%
2 14513
9.2%
13651
 
8.7%
; 12694
 
8.1%
8 11928
 
7.6%
C 9870
 
6.3%
M 9201
 
5.8%
T 8674
 
5.5%
4 7381
 
4.7%
Other values (62) 34692
22.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 157380
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 18832
12.0%
- 15944
10.1%
2 14513
9.2%
13651
 
8.7%
; 12694
 
8.1%
8 11928
 
7.6%
C 9870
 
6.3%
M 9201
 
5.8%
T 8674
 
5.5%
4 7381
 
4.7%
Other values (62) 34692
22.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 157380
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 18832
12.0%
- 15944
10.1%
2 14513
9.2%
13651
 
8.7%
; 12694
 
8.1%
8 11928
 
7.6%
C 9870
 
6.3%
M 9201
 
5.8%
T 8674
 
5.5%
4 7381
 
4.7%
Other values (62) 34692
22.0%

eventDate
Text

Missing 

Distinct17205
Distinct (%)6.9%
Missing474561
Missing (%)65.5%
Memory size5.5 MiB
2025-01-07T11:05:41.620083image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length10
Mean length7.503406722
Min length4

Characters and Unicode

Total characters1875454
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5657 ?
Unique (%)2.3%

Sample

1st row1985-01-23
2nd row1974
3rd row1980
4th row1963
5th row1956
ValueCountFrequency (%)
1999 3773
 
1.5%
1980 3743
 
1.5%
1982 3572
 
1.4%
1984-02 3350
 
1.3%
1998 3320
 
1.3%
1997 3308
 
1.3%
1995 3121
 
1.2%
2001 2935
 
1.2%
1974 2850
 
1.1%
1971 2519
 
1.0%
Other values (17195) 217456
87.0%
2025-01-07T11:05:41.884296image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 389845
20.8%
9 321056
17.1%
- 287687
15.3%
0 240421
12.8%
8 128673
 
6.9%
7 115893
 
6.2%
2 104754
 
5.6%
6 84492
 
4.5%
4 67249
 
3.6%
5 66574
 
3.5%
Other values (2) 68810
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1875454
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 389845
20.8%
9 321056
17.1%
- 287687
15.3%
0 240421
12.8%
8 128673
 
6.9%
7 115893
 
6.2%
2 104754
 
5.6%
6 84492
 
4.5%
4 67249
 
3.6%
5 66574
 
3.5%
Other values (2) 68810
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1875454
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 389845
20.8%
9 321056
17.1%
- 287687
15.3%
0 240421
12.8%
8 128673
 
6.9%
7 115893
 
6.2%
2 104754
 
5.6%
6 84492
 
4.5%
4 67249
 
3.6%
5 66574
 
3.5%
Other values (2) 68810
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1875454
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 389845
20.8%
9 321056
17.1%
- 287687
15.3%
0 240421
12.8%
8 128673
 
6.9%
7 115893
 
6.2%
2 104754
 
5.6%
6 84492
 
4.5%
4 67249
 
3.6%
5 66574
 
3.5%
Other values (2) 68810
 
3.7%

eventTime
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

startDayOfYear
Real number (ℝ)

Missing 

Distinct366
Distinct (%)0.3%
Missing593923
Missing (%)82.0%
Infinite0
Infinite (%)0.0%
Mean192.2771605
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:41.961965image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile48
Q1137
median201
Q3248
95-th percentile310
Maximum366
Range365
Interquartile range (IQR)111

Descriptive statistics

Standard deviation78.76365518
Coefficient of variation (CV)0.409636043
Kurtosis-0.5202115862
Mean192.2771605
Median Absolute Deviation (MAD)56
Skewness-0.3074105143
Sum25108513
Variance6203.713378
MonotonicityNot monotonic
2025-01-07T11:05:42.025950image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198 1192
 
0.2%
191 1146
 
0.2%
195 1139
 
0.2%
223 1099
 
0.2%
196 1078
 
0.1%
194 1065
 
0.1%
251 1041
 
0.1%
138 995
 
0.1%
137 971
 
0.1%
136 949
 
0.1%
Other values (356) 119910
 
16.6%
(Missing) 593923
82.0%
ValueCountFrequency (%)
1 20
 
< 0.1%
2 59
 
< 0.1%
3 24
 
< 0.1%
4 125
< 0.1%
5 150
< 0.1%
ValueCountFrequency (%)
366 8
 
< 0.1%
365 19
< 0.1%
364 22
< 0.1%
363 29
< 0.1%
362 8
 
< 0.1%

endDayOfYear
Real number (ℝ)

Missing 

Distinct366
Distinct (%)0.3%
Missing593923
Missing (%)82.0%
Infinite0
Infinite (%)0.0%
Mean192.4239844
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:42.087205image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile49
Q1137
median201
Q3248
95-th percentile310
Maximum366
Range365
Interquartile range (IQR)111

Descriptive statistics

Standard deviation78.66872144
Coefficient of variation (CV)0.4088301242
Kurtosis-0.526737264
Mean192.4239844
Median Absolute Deviation (MAD)56
Skewness-0.3026076446
Sum25127686
Variance6188.767733
MonotonicityNot monotonic
2025-01-07T11:05:42.217729image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198 1191
 
0.2%
191 1141
 
0.2%
195 1132
 
0.2%
196 1085
 
0.1%
194 1066
 
0.1%
251 1041
 
0.1%
138 996
 
0.1%
137 969
 
0.1%
136 949
 
0.1%
203 935
 
0.1%
Other values (356) 120080
 
16.6%
(Missing) 593923
82.0%
ValueCountFrequency (%)
1 20
 
< 0.1%
2 58
 
< 0.1%
3 24
 
< 0.1%
4 125
< 0.1%
5 150
< 0.1%
ValueCountFrequency (%)
366 8
 
< 0.1%
365 19
< 0.1%
364 23
< 0.1%
363 27
< 0.1%
362 8
 
< 0.1%

year
Real number (ℝ)

Missing 

Distinct190
Distinct (%)0.1%
Missing474684
Missing (%)65.5%
Infinite0
Infinite (%)0.0%
Mean1960.539007
Minimum1805
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:42.282664image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1805
5-th percentile1900
Q11941
median1970
Q31982
95-th percentile1998
Maximum2023
Range218
Interquartile range (IQR)41

Descriptive statistics

Standard deviation30.37698185
Coefficient of variation (CV)0.01549419916
Kurtosis0.1001964871
Mean1960.539007
Median Absolute Deviation (MAD)16
Skewness-0.9196027756
Sum489789697
Variance922.7610263
MonotonicityNot monotonic
2025-01-07T11:05:42.342170image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1980 7356
 
1.0%
1981 7186
 
1.0%
1982 7123
 
1.0%
1976 6483
 
0.9%
1971 6407
 
0.9%
1973 5775
 
0.8%
1984 5606
 
0.8%
1974 5415
 
0.7%
1999 5014
 
0.7%
1987 4898
 
0.7%
Other values (180) 188561
 
26.0%
(Missing) 474684
65.5%
ValueCountFrequency (%)
1805 1
 
< 0.1%
1810 1
 
< 0.1%
1817 1
 
< 0.1%
1823 9
< 0.1%
1824 1
 
< 0.1%
ValueCountFrequency (%)
2023 1
 
< 0.1%
2022 1
 
< 0.1%
2021 1
 
< 0.1%
2020 15
< 0.1%
2019 6
 
< 0.1%

month
Real number (ℝ)

Missing 

Distinct12
Distinct (%)< 0.1%
Missing572740
Missing (%)79.1%
Infinite0
Infinite (%)0.0%
Mean6.718583628
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:42.391746image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median7
Q39
95-th percentile11
Maximum12
Range11
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.66173107
Coefficient of variation (CV)0.3961744346
Kurtosis-0.5834458529
Mean6.718583628
Median Absolute Deviation (MAD)2
Skewness-0.2828535196
Sum1019666
Variance7.084812289
MonotonicityNot monotonic
2025-01-07T11:05:42.438249image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 25644
 
3.5%
7 25351
 
3.5%
6 14941
 
2.1%
5 14611
 
2.0%
10 14469
 
2.0%
9 14237
 
2.0%
4 11303
 
1.6%
2 8497
 
1.2%
3 8211
 
1.1%
11 6642
 
0.9%
Other values (2) 7862
 
1.1%
(Missing) 572740
79.1%
ValueCountFrequency (%)
1 4792
 
0.7%
2 8497
1.2%
3 8211
1.1%
4 11303
1.6%
5 14611
2.0%
ValueCountFrequency (%)
12 3070
 
0.4%
11 6642
 
0.9%
10 14469
2.0%
9 14237
2.0%
8 25644
3.5%

day
Real number (ℝ)

Missing 

Distinct31
Distinct (%)< 0.1%
Missing596444
Missing (%)82.3%
Infinite0
Infinite (%)0.0%
Mean15.82372876
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:42.486385image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q19
median16
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.581155667
Coefficient of variation (CV)0.542296686
Kurtosis-1.116069344
Mean15.82372876
Median Absolute Deviation (MAD)7
Skewness-0.00373108911
Sum2026450
Variance73.63623258
MonotonicityNot monotonic
2025-01-07T11:05:42.542411image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
17 5139
 
0.7%
16 4975
 
0.7%
18 4960
 
0.7%
13 4630
 
0.6%
20 4577
 
0.6%
23 4547
 
0.6%
8 4524
 
0.6%
14 4502
 
0.6%
15 4418
 
0.6%
10 4351
 
0.6%
Other values (21) 81441
 
11.2%
(Missing) 596444
82.3%
ValueCountFrequency (%)
1 3812
0.5%
2 4062
0.6%
3 3807
0.5%
4 3694
0.5%
5 3756
0.5%
ValueCountFrequency (%)
31 2241
0.3%
30 3914
0.5%
29 3746
0.5%
28 4135
0.6%
27 4079
0.6%

verbatimEventDate
Text

Missing 

Distinct17805
Distinct (%)6.4%
Missing445814
Missing (%)61.5%
Memory size5.5 MiB
2025-01-07T11:05:42.712904image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length61
Median length11
Mean length11.41229808
Min length4

Characters and Unicode

Total characters3180539
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5871 ?
Unique (%)2.1%

Sample

1st row23 JAN 1985
2nd rowApril, 1928
3rd row-- --- 1980
4th row-- --- 1963
5th row-- --- 1956
ValueCountFrequency (%)
235730
28.9%
aug 23677
 
2.9%
jul 22916
 
2.8%
summer 20031
 
2.5%
jun 14619
 
1.8%
may 14325
 
1.8%
oct 14287
 
1.7%
to 13955
 
1.7%
sep 13176
 
1.6%
apr 10764
 
1.3%
Other values (1210) 433163
53.0%
2025-01-07T11:05:42.970718image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 633590
19.9%
537949
16.9%
1 382844
12.0%
9 314473
9.9%
8 105770
 
3.3%
0 101858
 
3.2%
7 96225
 
3.0%
2 94879
 
3.0%
6 69663
 
2.2%
A 63864
 
2.0%
Other values (59) 779424
24.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3180539
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 633590
19.9%
537949
16.9%
1 382844
12.0%
9 314473
9.9%
8 105770
 
3.3%
0 101858
 
3.2%
7 96225
 
3.0%
2 94879
 
3.0%
6 69663
 
2.2%
A 63864
 
2.0%
Other values (59) 779424
24.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3180539
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 633590
19.9%
537949
16.9%
1 382844
12.0%
9 314473
9.9%
8 105770
 
3.3%
0 101858
 
3.2%
7 96225
 
3.0%
2 94879
 
3.0%
6 69663
 
2.2%
A 63864
 
2.0%
Other values (59) 779424
24.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3180539
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 633590
19.9%
537949
16.9%
1 382844
12.0%
9 314473
9.9%
8 105770
 
3.3%
0 101858
 
3.2%
7 96225
 
3.0%
2 94879
 
3.0%
6 69663
 
2.2%
A 63864
 
2.0%
Other values (59) 779424
24.5%

habitat
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

samplingProtocol
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

sampleSizeValue
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

sampleSizeUnit
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

samplingEffort
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

fieldNotes
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

eventRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

locationID
Text

Missing 

Distinct66560
Distinct (%)17.1%
Missing335037
Missing (%)46.2%
Memory size5.5 MiB
2025-01-07T11:05:43.173173image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length61
Median length59
Mean length5.757204002
Min length1

Characters and Unicode

Total characters2242264
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40451 ?
Unique (%)10.4%

Sample

1st row1612
2nd row06
3rd rowUSGS LOC M533
4th row42246
5th row707A
ValueCountFrequency (%)
42246 30863
 
6.4%
35k 30551
 
6.3%
loc 19929
 
4.1%
sta 7656
 
1.6%
d 5640
 
1.2%
site 4020
 
0.8%
40193 3269
 
0.7%
leg 3132
 
0.7%
olson 2904
 
0.6%
41142 2897
 
0.6%
Other values (59519) 370823
77.0%
2025-01-07T11:05:43.447424image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 252324
 
11.3%
1 209625
 
9.3%
4 194523
 
8.7%
3 152357
 
6.8%
0 140257
 
6.3%
5 136706
 
6.1%
6 130433
 
5.8%
7 107242
 
4.8%
8 99787
 
4.5%
9 93127
 
4.2%
Other values (71) 725883
32.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2242264
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 252324
 
11.3%
1 209625
 
9.3%
4 194523
 
8.7%
3 152357
 
6.8%
0 140257
 
6.3%
5 136706
 
6.1%
6 130433
 
5.8%
7 107242
 
4.8%
8 99787
 
4.5%
9 93127
 
4.2%
Other values (71) 725883
32.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2242264
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 252324
 
11.3%
1 209625
 
9.3%
4 194523
 
8.7%
3 152357
 
6.8%
0 140257
 
6.3%
5 136706
 
6.1%
6 130433
 
5.8%
7 107242
 
4.8%
8 99787
 
4.5%
9 93127
 
4.2%
Other values (71) 725883
32.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2242264
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 252324
 
11.3%
1 209625
 
9.3%
4 194523
 
8.7%
3 152357
 
6.8%
0 140257
 
6.3%
5 136706
 
6.1%
6 130433
 
5.8%
7 107242
 
4.8%
8 99787
 
4.5%
9 93127
 
4.2%
Other values (71) 725883
32.4%

higherGeographyID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

higherGeography
Text

Missing 

Distinct4708
Distinct (%)0.8%
Missing148417
Missing (%)20.5%
Memory size5.5 MiB
2025-01-07T11:05:43.643567image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length111
Median length97
Mean length42.17362361
Min length4

Characters and Unicode

Total characters24295845
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1213 ?
Unique (%)0.2%

Sample

1st rowNorth America, United States, Florida
2nd rowAfrica, Kenya, Marsabit
3rd rowNorth America, United States, Nevada, Pershing County
4th rowCuba, Camaguey Prov
5th rowNorth America, United States, North Carolina, Beaufort County
ValueCountFrequency (%)
north 537307
16.4%
america 480121
14.7%
united 421781
12.9%
states 421705
12.9%
county 259124
 
7.9%
carolina 46843
 
1.4%
canada 38942
 
1.2%
texas 38273
 
1.2%
colorado 35917
 
1.1%
beaufort 33680
 
1.0%
Other values (2951) 959718
29.3%
2025-01-07T11:05:43.904763image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2697320
 
11.1%
t 2343978
 
9.6%
a 2051368
 
8.4%
e 1823223
 
7.5%
i 1571709
 
6.5%
r 1497295
 
6.2%
o 1387848
 
5.7%
, 1279367
 
5.3%
n 1260166
 
5.2%
s 766919
 
3.2%
Other values (58) 7616652
31.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 24295845
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2697320
 
11.1%
t 2343978
 
9.6%
a 2051368
 
8.4%
e 1823223
 
7.5%
i 1571709
 
6.5%
r 1497295
 
6.2%
o 1387848
 
5.7%
, 1279367
 
5.3%
n 1260166
 
5.2%
s 766919
 
3.2%
Other values (58) 7616652
31.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 24295845
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2697320
 
11.1%
t 2343978
 
9.6%
a 2051368
 
8.4%
e 1823223
 
7.5%
i 1571709
 
6.5%
r 1497295
 
6.2%
o 1387848
 
5.7%
, 1279367
 
5.3%
n 1260166
 
5.2%
s 766919
 
3.2%
Other values (58) 7616652
31.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 24295845
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2697320
 
11.1%
t 2343978
 
9.6%
a 2051368
 
8.4%
e 1823223
 
7.5%
i 1571709
 
6.5%
r 1497295
 
6.2%
o 1387848
 
5.7%
, 1279367
 
5.3%
n 1260166
 
5.2%
s 766919
 
3.2%
Other values (58) 7616652
31.3%

continent
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing195168
Missing (%)26.9%
Memory size5.5 MiB
2025-01-07T11:05:43.963762image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.51518684
Min length4

Characters and Unicode

Total characters6624789
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowAFRICA
3rd rowNORTH_AMERICA
4th rowNORTH_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 480938
90.9%
south_america 11223
 
2.1%
europe 9975
 
1.9%
asia 9042
 
1.7%
oceania 8130
 
1.5%
africa 6638
 
1.3%
antarctica 3394
 
0.6%
2025-01-07T11:05:44.059634image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1042124
15.7%
R 993106
15.0%
E 520241
7.9%
I 519365
7.8%
C 513717
7.8%
O 510266
7.7%
T 498949
7.5%
N 492462
7.4%
H 492161
7.4%
_ 492161
7.4%
Other values (5) 550237
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6624789
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 1042124
15.7%
R 993106
15.0%
E 520241
7.9%
I 519365
7.8%
C 513717
7.8%
O 510266
7.7%
T 498949
7.5%
N 492462
7.4%
H 492161
7.4%
_ 492161
7.4%
Other values (5) 550237
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6624789
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 1042124
15.7%
R 993106
15.0%
E 520241
7.9%
I 519365
7.8%
C 513717
7.8%
O 510266
7.7%
T 498949
7.5%
N 492462
7.4%
H 492161
7.4%
_ 492161
7.4%
Other values (5) 550237
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6624789
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 1042124
15.7%
R 993106
15.0%
E 520241
7.9%
I 519365
7.8%
C 513717
7.8%
O 510266
7.7%
T 498949
7.5%
N 492462
7.4%
H 492161
7.4%
_ 492161
7.4%
Other values (5) 550237
8.3%

waterBody
Text

Missing 

Distinct172
Distinct (%)0.6%
Missing696851
Missing (%)96.2%
Memory size5.5 MiB
2025-01-07T11:05:44.163029image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length61
Median length54
Mean length21.95758759
Min length8

Characters and Unicode

Total characters607281
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)0.2%

Sample

1st rowNorth Atlantic Ocean
2nd rowNorth Pacific Ocean
3rd rowNorth Atlantic Ocean, Caribbean Sea
4th rowNorth Atlantic Ocean
5th rowNorth Atlantic Ocean
ValueCountFrequency (%)
ocean 26667
28.1%
north 18835
19.9%
atlantic 13621
14.4%
pacific 8356
 
8.8%
sea 5778
 
6.1%
indian 4034
 
4.3%
south 2993
 
3.2%
timor 2479
 
2.6%
of 2181
 
2.3%
gulf 2067
 
2.2%
Other values (146) 7758
 
8.2%
2025-01-07T11:05:44.340093image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67112
11.1%
a 66029
10.9%
c 60399
9.9%
n 52729
 
8.7%
t 51240
 
8.4%
i 42959
 
7.1%
e 39252
 
6.5%
o 28732
 
4.7%
O 27050
 
4.5%
r 26329
 
4.3%
Other values (39) 145450
24.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 607281
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
67112
11.1%
a 66029
10.9%
c 60399
9.9%
n 52729
 
8.7%
t 51240
 
8.4%
i 42959
 
7.1%
e 39252
 
6.5%
o 28732
 
4.7%
O 27050
 
4.5%
r 26329
 
4.3%
Other values (39) 145450
24.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 607281
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
67112
11.1%
a 66029
10.9%
c 60399
9.9%
n 52729
 
8.7%
t 51240
 
8.4%
i 42959
 
7.1%
e 39252
 
6.5%
o 28732
 
4.7%
O 27050
 
4.5%
r 26329
 
4.3%
Other values (39) 145450
24.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 607281
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
67112
11.1%
a 66029
10.9%
c 60399
9.9%
n 52729
 
8.7%
t 51240
 
8.4%
i 42959
 
7.1%
e 39252
 
6.5%
o 28732
 
4.7%
O 27050
 
4.5%
r 26329
 
4.3%
Other values (39) 145450
24.0%

islandGroup
Text

Missing 

Distinct33
Distinct (%)4.1%
Missing723710
Missing (%)99.9%
Memory size5.5 MiB
2025-01-07T11:05:44.410227image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length24
Mean length16.78571429
Min length5

Characters and Unicode

Total characters13395
Distinct characters46
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)1.6%

Sample

1st rowMariana Islands
2nd rowNorthern Mariana Islands
3rd rowGilbert Islands
4th rowGilbert Islands
5th rowAleutian Islands
ValueCountFrequency (%)
islands 765
44.5%
marshall 241
 
14.0%
mariana 155
 
9.0%
gilbert 135
 
7.9%
northern 134
 
7.8%
marianas 120
 
7.0%
solomon 21
 
1.2%
hawaiian 18
 
1.0%
ryukyu 18
 
1.0%
antilles 15
 
0.9%
Other values (26) 97
 
5.6%
2025-01-07T11:05:44.546206image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2202
16.4%
s 1936
14.5%
l 1461
10.9%
n 1270
9.5%
r 960
7.2%
921
6.9%
d 800
 
6.0%
I 765
 
5.7%
M 527
 
3.9%
i 498
 
3.7%
Other values (36) 2055
15.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13395
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2202
16.4%
s 1936
14.5%
l 1461
10.9%
n 1270
9.5%
r 960
7.2%
921
6.9%
d 800
 
6.0%
I 765
 
5.7%
M 527
 
3.9%
i 498
 
3.7%
Other values (36) 2055
15.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13395
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2202
16.4%
s 1936
14.5%
l 1461
10.9%
n 1270
9.5%
r 960
7.2%
921
6.9%
d 800
 
6.0%
I 765
 
5.7%
M 527
 
3.9%
i 498
 
3.7%
Other values (36) 2055
15.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13395
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2202
16.4%
s 1936
14.5%
l 1461
10.9%
n 1270
9.5%
r 960
7.2%
921
6.9%
d 800
 
6.0%
I 765
 
5.7%
M 527
 
3.9%
i 498
 
3.7%
Other values (36) 2055
15.3%

island
Text

Missing 

Distinct87
Distinct (%)0.9%
Missing714401
Missing (%)98.6%
Memory size5.5 MiB
2025-01-07T11:05:44.621119image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length4
Mean length6.015335906
Min length3

Characters and Unicode

Total characters60797
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)0.4%

Sample

1st rowOahu
2nd rowOahu
3rd rowOahu
4th rowAnimasola Island
5th rowMolokai
ValueCountFrequency (%)
oahu 5926
51.1%
molokai 2218
 
19.1%
saint 944
 
8.1%
helena 938
 
8.1%
atoll 241
 
2.1%
saipan 132
 
1.1%
guam 129
 
1.1%
onotoa 116
 
1.0%
martha's 108
 
0.9%
vineyard 108
 
0.9%
Other values (91) 728
 
6.3%
2025-01-07T11:05:44.762146image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 11360
18.7%
u 6232
10.3%
h 6099
10.0%
O 6043
9.9%
o 5165
8.5%
i 4062
 
6.7%
l 3813
 
6.3%
n 2689
 
4.4%
k 2476
 
4.1%
M 2342
 
3.9%
Other values (40) 10516
17.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 60797
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 11360
18.7%
u 6232
10.3%
h 6099
10.0%
O 6043
9.9%
o 5165
8.5%
i 4062
 
6.7%
l 3813
 
6.3%
n 2689
 
4.4%
k 2476
 
4.1%
M 2342
 
3.9%
Other values (40) 10516
17.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 60797
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 11360
18.7%
u 6232
10.3%
h 6099
10.0%
O 6043
9.9%
o 5165
8.5%
i 4062
 
6.7%
l 3813
 
6.3%
n 2689
 
4.4%
k 2476
 
4.1%
M 2342
 
3.9%
Other values (40) 10516
17.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 60797
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 11360
18.7%
u 6232
10.3%
h 6099
10.0%
O 6043
9.9%
o 5165
8.5%
i 4062
 
6.7%
l 3813
 
6.3%
n 2689
 
4.4%
k 2476
 
4.1%
M 2342
 
3.9%
Other values (40) 10516
17.3%

countryCode
Text

Missing 

Distinct185
Distinct (%)< 0.1%
Missing158422
Missing (%)21.9%
Memory size5.5 MiB
2025-01-07T11:05:44.903770image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1132172
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)< 0.1%

Sample

1st rowUS
2nd rowKE
3rd rowUS
4th rowCU
5th rowUS
ValueCountFrequency (%)
us 428942
75.8%
ca 39076
 
6.9%
pa 8629
 
1.5%
do 6290
 
1.1%
mx 3952
 
0.7%
co 3623
 
0.6%
fr 3541
 
0.6%
aq 3460
 
0.6%
cr 3282
 
0.6%
pr 3114
 
0.6%
Other values (175) 62177
 
11.0%
2025-01-07T11:05:45.090942image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 434999
38.4%
S 434979
38.4%
A 57869
 
5.1%
C 53653
 
4.7%
P 19200
 
1.7%
E 14200
 
1.3%
R 12973
 
1.1%
O 11631
 
1.0%
D 10040
 
0.9%
M 9508
 
0.8%
Other values (16) 73120
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1132172
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 434999
38.4%
S 434979
38.4%
A 57869
 
5.1%
C 53653
 
4.7%
P 19200
 
1.7%
E 14200
 
1.3%
R 12973
 
1.1%
O 11631
 
1.0%
D 10040
 
0.9%
M 9508
 
0.8%
Other values (16) 73120
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1132172
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 434999
38.4%
S 434979
38.4%
A 57869
 
5.1%
C 53653
 
4.7%
P 19200
 
1.7%
E 14200
 
1.3%
R 12973
 
1.1%
O 11631
 
1.0%
D 10040
 
0.9%
M 9508
 
0.8%
Other values (16) 73120
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1132172
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 434999
38.4%
S 434979
38.4%
A 57869
 
5.1%
C 53653
 
4.7%
P 19200
 
1.7%
E 14200
 
1.3%
R 12973
 
1.1%
O 11631
 
1.0%
D 10040
 
0.9%
M 9508
 
0.8%
Other values (16) 73120
 
6.5%

stateProvince
Text

Missing 

Distinct892
Distinct (%)0.2%
Missing226462
Missing (%)31.3%
Memory size5.5 MiB
2025-01-07T11:05:45.286789image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length23
Mean length8.789222281
Min length3

Characters and Unicode

Total characters4377437
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique236 ?
Unique (%)< 0.1%

Sample

1st rowFlorida
2nd rowMarsabit
3rd rowNevada
4th rowCamaguey Prov
5th rowNorth Carolina
ValueCountFrequency (%)
carolina 46813
 
7.5%
north 45129
 
7.2%
texas 38253
 
6.1%
colorado 35917
 
5.8%
california 32474
 
5.2%
columbia 32203
 
5.2%
british 32085
 
5.1%
alaska 28545
 
4.6%
new 23155
 
3.7%
wyoming 22778
 
3.6%
Other values (878) 287106
46.0%
2025-01-07T11:05:45.543235image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 622536
14.2%
i 445132
 
10.2%
o 412678
 
9.4%
r 299951
 
6.9%
n 262321
 
6.0%
l 249350
 
5.7%
s 213346
 
4.9%
e 190372
 
4.3%
C 155417
 
3.6%
t 143584
 
3.3%
Other values (54) 1382750
31.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4377437
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 622536
14.2%
i 445132
 
10.2%
o 412678
 
9.4%
r 299951
 
6.9%
n 262321
 
6.0%
l 249350
 
5.7%
s 213346
 
4.9%
e 190372
 
4.3%
C 155417
 
3.6%
t 143584
 
3.3%
Other values (54) 1382750
31.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4377437
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 622536
14.2%
i 445132
 
10.2%
o 412678
 
9.4%
r 299951
 
6.9%
n 262321
 
6.0%
l 249350
 
5.7%
s 213346
 
4.9%
e 190372
 
4.3%
C 155417
 
3.6%
t 143584
 
3.3%
Other values (54) 1382750
31.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4377437
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 622536
14.2%
i 445132
 
10.2%
o 412678
 
9.4%
r 299951
 
6.9%
n 262321
 
6.0%
l 249350
 
5.7%
s 213346
 
4.9%
e 190372
 
4.3%
C 155417
 
3.6%
t 143584
 
3.3%
Other values (54) 1382750
31.6%

county
Text

Missing 

Distinct1997
Distinct (%)0.7%
Missing454433
Missing (%)62.7%
Memory size5.5 MiB
2025-01-07T11:05:45.734329image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length34
Median length29
Mean length14.2528779
Min length3

Characters and Unicode

Total characters3849346
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique393 ?
Unique (%)0.1%

Sample

1st rowPershing County
2nd rowBeaufort County
3rd rowBrewster County
4th rowLos Angeles County
5th rowHonolulu County
ValueCountFrequency (%)
county 259124
45.6%
beaufort 33592
 
5.9%
brewster 15677
 
2.8%
maui 10401
 
1.8%
los 8883
 
1.6%
angeles 8865
 
1.6%
honolulu 5926
 
1.0%
san 4953
 
0.9%
lincoln 4346
 
0.8%
culberson 4132
 
0.7%
Other values (1945) 212334
37.4%
2025-01-07T11:05:46.058728image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 423340
11.0%
n 401510
10.4%
t 375302
9.7%
u 352655
9.2%
298158
 
7.7%
C 289740
 
7.5%
y 279783
 
7.3%
e 215178
 
5.6%
a 186491
 
4.8%
r 177010
 
4.6%
Other values (55) 850179
22.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3849346
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 423340
11.0%
n 401510
10.4%
t 375302
9.7%
u 352655
9.2%
298158
 
7.7%
C 289740
 
7.5%
y 279783
 
7.3%
e 215178
 
5.6%
a 186491
 
4.8%
r 177010
 
4.6%
Other values (55) 850179
22.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3849346
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 423340
11.0%
n 401510
10.4%
t 375302
9.7%
u 352655
9.2%
298158
 
7.7%
C 289740
 
7.5%
y 279783
 
7.3%
e 215178
 
5.6%
a 186491
 
4.8%
r 177010
 
4.6%
Other values (55) 850179
22.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3849346
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 423340
11.0%
n 401510
10.4%
t 375302
9.7%
u 352655
9.2%
298158
 
7.7%
C 289740
 
7.5%
y 279783
 
7.3%
e 215178
 
5.6%
a 186491
 
4.8%
r 177010
 
4.6%
Other values (55) 850179
22.1%

municipality
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

locality
Text

Missing 

Distinct31755
Distinct (%)19.4%
Missing560871
Missing (%)77.4%
Memory size5.5 MiB
2025-01-07T11:05:46.258277image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length471
Median length316
Mean length59.79365302
Min length1

Characters and Unicode

Total characters9784454
Distinct characters100
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21088 ?
Unique (%)12.9%

Sample

1st rowSt. Andrew Bay
2nd rowNuevitas Bay, Between Nuevitas And Pastelillo
3rd rowPalos Verdes Hills; East side of Deadman's Island
4th rowNorth slope of San Pedro Hills, ravine S of harbor City, 4200 feet N and 53.5 degrees E from 342-foot hill, 100 feet up ravine from end of Bellepoint Street (W98-30)
5th rowCoyote Springs Valley; spring
ValueCountFrequency (%)
of 120156
 
7.0%
34919
 
2.0%
and 22265
 
1.3%
bay 19665
 
1.1%
the 18421
 
1.1%
on 17778
 
1.0%
from 16823
 
1.0%
n 16777
 
1.0%
feet 15757
 
0.9%
river 15334
 
0.9%
Other values (34131) 1421831
82.7%
2025-01-07T11:05:46.518528image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1556089
 
15.9%
e 696401
 
7.1%
a 667613
 
6.8%
o 563197
 
5.8%
n 459256
 
4.7%
t 454549
 
4.6%
r 411335
 
4.2%
i 400968
 
4.1%
l 325764
 
3.3%
s 321160
 
3.3%
Other values (90) 3928122
40.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9784454
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1556089
 
15.9%
e 696401
 
7.1%
a 667613
 
6.8%
o 563197
 
5.8%
n 459256
 
4.7%
t 454549
 
4.6%
r 411335
 
4.2%
i 400968
 
4.1%
l 325764
 
3.3%
s 321160
 
3.3%
Other values (90) 3928122
40.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9784454
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1556089
 
15.9%
e 696401
 
7.1%
a 667613
 
6.8%
o 563197
 
5.8%
n 459256
 
4.7%
t 454549
 
4.6%
r 411335
 
4.2%
i 400968
 
4.1%
l 325764
 
3.3%
s 321160
 
3.3%
Other values (90) 3928122
40.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9784454
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1556089
 
15.9%
e 696401
 
7.1%
a 667613
 
6.8%
o 563197
 
5.8%
n 459256
 
4.7%
t 454549
 
4.6%
r 411335
 
4.2%
i 400968
 
4.1%
l 325764
 
3.3%
s 321160
 
3.3%
Other values (90) 3928122
40.1%

verbatimLocality
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

verbatimElevation
Text

Missing 

Distinct7
Distinct (%)3.6%
Missing724311
Missing (%)> 99.9%
Memory size5.5 MiB
2025-01-07T11:05:46.615273image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length88
Median length88
Mean length81.14720812
Min length8

Characters and Unicode

Total characters15986
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.0%

Sample

1st rowElevation for Rampart Cave derived from Google Earth by Dr. Jim Mead on 4 Decemeber 2023
2nd rowApprox.450-500ft Above Base Of Fm
3rd rowElevation for Rampart Cave derived from Google Earth by Dr. Jim Mead on 4 Decemeber 2023
4th rowElevation for Rampart Cave derived from Google Earth by Dr. Jim Mead on 4 Decemeber 2023
5th rowElevation for Rampart Cave derived from Google Earth by Dr. Jim Mead on 4 Decemeber 2023
ValueCountFrequency (%)
elevation 161
 
5.5%
for 161
 
5.5%
rampart 161
 
5.5%
cave 161
 
5.5%
derived 161
 
5.5%
from 161
 
5.5%
google 161
 
5.5%
earth 161
 
5.5%
by 161
 
5.5%
dr 161
 
5.5%
Other values (38) 1300
44.7%
2025-01-07T11:05:46.778455image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2713
17.0%
e 1696
 
10.6%
r 1185
 
7.4%
o 1092
 
6.8%
a 1023
 
6.4%
m 656
 
4.1%
t 562
 
3.5%
v 533
 
3.3%
i 527
 
3.3%
d 497
 
3.1%
Other values (45) 5502
34.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15986
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2713
17.0%
e 1696
 
10.6%
r 1185
 
7.4%
o 1092
 
6.8%
a 1023
 
6.4%
m 656
 
4.1%
t 562
 
3.5%
v 533
 
3.3%
i 527
 
3.3%
d 497
 
3.1%
Other values (45) 5502
34.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15986
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2713
17.0%
e 1696
 
10.6%
r 1185
 
7.4%
o 1092
 
6.8%
a 1023
 
6.4%
m 656
 
4.1%
t 562
 
3.5%
v 533
 
3.3%
i 527
 
3.3%
d 497
 
3.1%
Other values (45) 5502
34.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15986
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2713
17.0%
e 1696
 
10.6%
r 1185
 
7.4%
o 1092
 
6.8%
a 1023
 
6.4%
m 656
 
4.1%
t 562
 
3.5%
v 533
 
3.3%
i 527
 
3.3%
d 497
 
3.1%
Other values (45) 5502
34.4%

verticalDatum
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

verbatimDepth
Text

Missing 

Distinct17
Distinct (%)20.2%
Missing724424
Missing (%)> 99.9%
Memory size5.5 MiB
2025-01-07T11:05:46.841892image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length10
Mean length5.523809524
Min length4

Characters and Unicode

Total characters464
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)10.7%

Sample

1st rowreef
2nd rowBeach
3rd row?48 Ms
4th rowBeach
5th rowIntertidal
ValueCountFrequency (%)
reef 30
27.5%
beach 25
22.9%
low 9
 
8.3%
ms 8
 
7.3%
water 7
 
6.4%
48 6
 
5.5%
no.4 4
 
3.7%
mnb 3
 
2.8%
57ms 2
 
1.8%
25 2
 
1.8%
Other values (12) 13
11.9%
2025-01-07T11:05:46.955127image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 96
20.7%
r 40
 
8.6%
a 37
 
8.0%
f 31
 
6.7%
c 26
 
5.6%
h 25
 
5.4%
25
 
5.4%
b 18
 
3.9%
t 13
 
2.8%
o 13
 
2.8%
Other values (30) 140
30.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 464
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 96
20.7%
r 40
 
8.6%
a 37
 
8.0%
f 31
 
6.7%
c 26
 
5.6%
h 25
 
5.4%
25
 
5.4%
b 18
 
3.9%
t 13
 
2.8%
o 13
 
2.8%
Other values (30) 140
30.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 464
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 96
20.7%
r 40
 
8.6%
a 37
 
8.0%
f 31
 
6.7%
c 26
 
5.6%
h 25
 
5.4%
25
 
5.4%
b 18
 
3.9%
t 13
 
2.8%
o 13
 
2.8%
Other values (30) 140
30.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 464
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 96
20.7%
r 40
 
8.6%
a 37
 
8.0%
f 31
 
6.7%
c 26
 
5.6%
h 25
 
5.4%
25
 
5.4%
b 18
 
3.9%
t 13
 
2.8%
o 13
 
2.8%
Other values (30) 140
30.2%

minimumDistanceAboveSurfaceInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

maximumDistanceAboveSurfaceInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

locationAccordingTo
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

locationRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

decimalLatitude
Real number (ℝ)

Missing 

Distinct34309
Distinct (%)33.0%
Missing620570
Missing (%)85.7%
Infinite0
Infinite (%)0.0%
Mean36.17761578
Minimum-77.9033
Maximum89.13
Zeros12
Zeros (%)< 0.1%
Negative5725
Negative (%)0.8%
Memory size5.5 MiB
2025-01-07T11:05:47.019275image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-77.9033
5-th percentile-9.0417
Q130.2267
median37.54725
Q345.743025
95-th percentile59.895255
Maximum89.13
Range167.0333
Interquartile range (IQR)15.516325

Descriptive statistics

Standard deviation18.98229075
Coefficient of variation (CV)0.5246971185
Kurtosis4.688030722
Mean36.17761578
Median Absolute Deviation (MAD)7.40415
Skewness-1.613703618
Sum3760229.028
Variance360.3273622
MonotonicityNot monotonic
2025-01-07T11:05:47.078249image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44.6458 1686
 
0.2%
17.5 673
 
0.1%
29.8119 329
 
< 0.1%
33.1767 323
 
< 0.1%
34.6405 307
 
< 0.1%
38.8295 287
 
< 0.1%
41.1458 279
 
< 0.1%
48.1104 243
 
< 0.1%
40.6184 235
 
< 0.1%
31.6767 227
 
< 0.1%
Other values (34299) 99349
 
13.7%
(Missing) 620570
85.7%
ValueCountFrequency (%)
-77.9033 5
 
< 0.1%
-77.58 1
 
< 0.1%
-77.57 5
 
< 0.1%
-77.5 15
< 0.1%
-76.98 1
 
< 0.1%
ValueCountFrequency (%)
89.13 3
 
< 0.1%
88.7817 9
< 0.1%
88.515 7
< 0.1%
88.0367 7
< 0.1%
87.75 7
< 0.1%

decimalLongitude
Real number (ℝ)

Missing 

Distinct35343
Distinct (%)34.0%
Missing620570
Missing (%)85.7%
Infinite0
Infinite (%)0.0%
Mean-84.45552615
Minimum-179.57
Maximum179.8
Zeros19
Zeros (%)< 0.1%
Negative95623
Negative (%)13.2%
Memory size5.5 MiB
2025-01-07T11:05:47.134758image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-179.57
5-th percentile-156.775
Q1-122.706
median-87.3072
Q3-75.610425
95-th percentile88.7181
Maximum179.8
Range359.37
Interquartile range (IQR)47.095575

Descriptive statistics

Standard deviation63.087641
Coefficient of variation (CV)-0.7469924571
Kurtosis5.28951012
Mean-84.45552615
Median Absolute Deviation (MAD)17.5088
Skewness2.138850984
Sum-8778138.477
Variance3980.050447
MonotonicityNot monotonic
2025-01-07T11:05:47.192500image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-123.908 1686
 
0.2%
-95.0833 673
 
0.1%
-103.252 329
 
< 0.1%
-98.6878 321
 
< 0.1%
-105.851 307
 
< 0.1%
-76.8473 287
 
< 0.1%
-115.358 279
 
< 0.1%
-123.934 243
 
< 0.1%
-108.207 235
 
< 0.1%
-123.18 230
 
< 0.1%
Other values (35333) 99348
 
13.7%
(Missing) 620570
85.7%
ValueCountFrequency (%)
-179.57 1
 
< 0.1%
-179.556 12
< 0.1%
-179.555 4
 
< 0.1%
-179.55 4
 
< 0.1%
-179 1
 
< 0.1%
ValueCountFrequency (%)
179.8 1
< 0.1%
179.58 1
< 0.1%
179.5 1
< 0.1%
179.137 2
< 0.1%
179.08 2
< 0.1%

coordinateUncertaintyInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

coordinatePrecision
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

pointRadiusSpatialFit
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

verbatimCoordinateSystem
Text

Constant  Missing 

Distinct1
Distinct (%)< 0.1%
Missing654265
Missing (%)90.3%
Memory size5.5 MiB
2025-01-07T11:05:47.234515image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters1615589
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDegrees Minutes Seconds
2nd rowDegrees Minutes Seconds
3rd rowDegrees Minutes Seconds
4th rowDegrees Minutes Seconds
5th rowDegrees Minutes Seconds
ValueCountFrequency (%)
degrees 70243
33.3%
minutes 70243
33.3%
seconds 70243
33.3%
2025-01-07T11:05:47.329502image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 351215
21.7%
s 210729
13.0%
140486
 
8.7%
n 140486
 
8.7%
g 70243
 
4.3%
r 70243
 
4.3%
D 70243
 
4.3%
M 70243
 
4.3%
i 70243
 
4.3%
u 70243
 
4.3%
Other values (5) 351215
21.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1615589
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 351215
21.7%
s 210729
13.0%
140486
 
8.7%
n 140486
 
8.7%
g 70243
 
4.3%
r 70243
 
4.3%
D 70243
 
4.3%
M 70243
 
4.3%
i 70243
 
4.3%
u 70243
 
4.3%
Other values (5) 351215
21.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1615589
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 351215
21.7%
s 210729
13.0%
140486
 
8.7%
n 140486
 
8.7%
g 70243
 
4.3%
r 70243
 
4.3%
D 70243
 
4.3%
M 70243
 
4.3%
i 70243
 
4.3%
u 70243
 
4.3%
Other values (5) 351215
21.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1615589
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 351215
21.7%
s 210729
13.0%
140486
 
8.7%
n 140486
 
8.7%
g 70243
 
4.3%
r 70243
 
4.3%
D 70243
 
4.3%
M 70243
 
4.3%
i 70243
 
4.3%
u 70243
 
4.3%
Other values (5) 351215
21.7%

verbatimSRS
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

footprintWKT
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

footprintSRS
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

footprintSpatialFit
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

georeferencedBy
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

georeferencedDate
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

georeferenceProtocol
Text

Missing 

Distinct19
Distinct (%)0.1%
Missing695012
Missing (%)95.9%
Memory size5.5 MiB
2025-01-07T11:05:47.402504image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length81
Median length43
Mean length42.23633713
Min length7

Characters and Unicode

Total characters1245803
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowGeoreferencing Quick Reference Guide (2020)
2nd rowGeoreferencing Quick Reference Guide (2020)
3rd rowGeoreferencing Quick Reference Guide (2020)
4th rowGeoreferencing Quick Reference Guide (2020)
5th rowGeoreferencing Quick Reference Guide (2020)
ValueCountFrequency (%)
georeferencing 26344
17.6%
guide 26344
17.6%
quick 24178
16.2%
reference 24178
16.2%
2020 24178
16.2%
to 2166
 
1.4%
best 2166
 
1.4%
practices 2166
 
1.4%
for 2166
 
1.4%
biogeomancer 2166
 
1.4%
Other values (32) 13421
9.0%
2025-01-07T11:05:47.540319image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 237471
19.1%
119977
 
9.6%
r 87730
 
7.0%
i 84069
 
6.7%
n 82720
 
6.6%
c 81302
 
6.5%
u 58822
 
4.7%
G 54854
 
4.4%
0 52731
 
4.2%
f 52688
 
4.2%
Other values (40) 333439
26.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1245803
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 237471
19.1%
119977
 
9.6%
r 87730
 
7.0%
i 84069
 
6.7%
n 82720
 
6.6%
c 81302
 
6.5%
u 58822
 
4.7%
G 54854
 
4.4%
0 52731
 
4.2%
f 52688
 
4.2%
Other values (40) 333439
26.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1245803
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 237471
19.1%
119977
 
9.6%
r 87730
 
7.0%
i 84069
 
6.7%
n 82720
 
6.6%
c 81302
 
6.5%
u 58822
 
4.7%
G 54854
 
4.4%
0 52731
 
4.2%
f 52688
 
4.2%
Other values (40) 333439
26.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1245803
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 237471
19.1%
119977
 
9.6%
r 87730
 
7.0%
i 84069
 
6.7%
n 82720
 
6.6%
c 81302
 
6.5%
u 58822
 
4.7%
G 54854
 
4.4%
0 52731
 
4.2%
f 52688
 
4.2%
Other values (40) 333439
26.8%

georeferenceSources
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

georeferenceRemarks
Text

Missing 

Distinct2
Distinct (%)40.0%
Missing724503
Missing (%)> 99.9%
Memory size5.5 MiB
2025-01-07T11:05:47.601025image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length70
Median length70
Mean length58
Min length10

Characters and Unicode

Total characters290
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st rowA; B; C; D
2nd rowincluded in Jennifer Jett's Foram Bulk DB but not included in F Ledger
3rd rowincluded in Jennifer Jett's Foram Bulk DB but not included in F Ledger
4th rowincluded in Jennifer Jett's Foram Bulk DB but not included in F Ledger
5th rowincluded in Jennifer Jett's Foram Bulk DB but not included in F Ledger
ValueCountFrequency (%)
included 8
14.3%
in 8
14.3%
jennifer 4
7.1%
jett's 4
7.1%
foram 4
7.1%
bulk 4
7.1%
db 4
7.1%
but 4
7.1%
not 4
7.1%
f 4
7.1%
Other values (5) 8
14.3%
2025-01-07T11:05:47.717400image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51
17.6%
e 28
 
9.7%
n 28
 
9.7%
d 20
 
6.9%
i 20
 
6.9%
u 16
 
5.5%
t 16
 
5.5%
r 12
 
4.1%
l 12
 
4.1%
B 9
 
3.1%
Other values (17) 78
26.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 290
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
51
17.6%
e 28
 
9.7%
n 28
 
9.7%
d 20
 
6.9%
i 20
 
6.9%
u 16
 
5.5%
t 16
 
5.5%
r 12
 
4.1%
l 12
 
4.1%
B 9
 
3.1%
Other values (17) 78
26.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 290
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
51
17.6%
e 28
 
9.7%
n 28
 
9.7%
d 20
 
6.9%
i 20
 
6.9%
u 16
 
5.5%
t 16
 
5.5%
r 12
 
4.1%
l 12
 
4.1%
B 9
 
3.1%
Other values (17) 78
26.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 290
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
51
17.6%
e 28
 
9.7%
n 28
 
9.7%
d 20
 
6.9%
i 20
 
6.9%
u 16
 
5.5%
t 16
 
5.5%
r 12
 
4.1%
l 12
 
4.1%
B 9
 
3.1%
Other values (17) 78
26.9%

geologicalContextID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

earliestEonOrLowestEonothem
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

latestEonOrHighestEonothem
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB
Distinct10
Distinct (%)< 0.1%
Missing220036
Missing (%)30.4%
Memory size5.5 MiB
2025-01-07T11:05:47.767400image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length8
Mean length8.387123567
Min length8

Characters and Unicode

Total characters4231069
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowMesozoic
2nd rowCenozoic
3rd rowCenozoic
4th rowPaleozoic
5th rowCenozoic
ValueCountFrequency (%)
cenozoic 261752
51.9%
paleozoic 194023
38.5%
mesozoic 48343
 
9.6%
precambrian 298
 
0.1%
mesoproterozoic 41
 
< 0.1%
neoproterozoic 7
 
< 0.1%
paleoproterozoic 4
 
< 0.1%
paleoarchean 3
 
< 0.1%
mesoarchean 1
 
< 0.1%
2025-01-07T11:05:47.881587image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1008448
23.8%
e 504528
11.9%
c 504472
11.9%
i 504468
11.9%
z 504170
11.9%
n 262054
 
6.2%
C 261752
 
6.2%
a 194634
 
4.6%
P 194327
 
4.6%
l 194030
 
4.6%
Other values (9) 98186
 
2.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4231069
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 1008448
23.8%
e 504528
11.9%
c 504472
11.9%
i 504468
11.9%
z 504170
11.9%
n 262054
 
6.2%
C 261752
 
6.2%
a 194634
 
4.6%
P 194327
 
4.6%
l 194030
 
4.6%
Other values (9) 98186
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4231069
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 1008448
23.8%
e 504528
11.9%
c 504472
11.9%
i 504468
11.9%
z 504170
11.9%
n 262054
 
6.2%
C 261752
 
6.2%
a 194634
 
4.6%
P 194327
 
4.6%
l 194030
 
4.6%
Other values (9) 98186
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4231069
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 1008448
23.8%
e 504528
11.9%
c 504472
11.9%
i 504468
11.9%
z 504170
11.9%
n 262054
 
6.2%
C 261752
 
6.2%
a 194634
 
4.6%
P 194327
 
4.6%
l 194030
 
4.6%
Other values (9) 98186
 
2.3%
Distinct5
Distinct (%)0.1%
Missing718163
Missing (%)99.1%
Memory size5.5 MiB
2025-01-07T11:05:47.930908image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length8
Mean length8.134121355
Min length8

Characters and Unicode

Total characters51611
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowPaleozoic
2nd rowCenozoic
3rd rowMesozoic
4th rowCenozoic
5th rowCenozoic
ValueCountFrequency (%)
cenozoic 5229
82.4%
paleozoic 826
 
13.0%
mesozoic 286
 
4.5%
neoproterozoic 3
 
< 0.1%
mesoproterozoic 1
 
< 0.1%
2025-01-07T11:05:48.038947image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 12698
24.6%
e 6349
12.3%
i 6345
12.3%
z 6345
12.3%
c 6345
12.3%
C 5229
10.1%
n 5229
10.1%
P 826
 
1.6%
a 826
 
1.6%
l 826
 
1.6%
Other values (6) 593
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 51611
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 12698
24.6%
e 6349
12.3%
i 6345
12.3%
z 6345
12.3%
c 6345
12.3%
C 5229
10.1%
n 5229
10.1%
P 826
 
1.6%
a 826
 
1.6%
l 826
 
1.6%
Other values (6) 593
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 51611
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 12698
24.6%
e 6349
12.3%
i 6345
12.3%
z 6345
12.3%
c 6345
12.3%
C 5229
10.1%
n 5229
10.1%
P 826
 
1.6%
a 826
 
1.6%
l 826
 
1.6%
Other values (6) 593
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 51611
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 12698
24.6%
e 6349
12.3%
i 6345
12.3%
z 6345
12.3%
c 6345
12.3%
C 5229
10.1%
n 5229
10.1%
P 826
 
1.6%
a 826
 
1.6%
l 826
 
1.6%
Other values (6) 593
 
1.1%
Distinct27
Distinct (%)< 0.1%
Missing245750
Missing (%)33.9%
Memory size5.5 MiB
2025-01-07T11:05:48.099844image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length10
Mean length8.607453035
Min length6

Characters and Unicode

Total characters4120887
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowTriassic
2nd rowPaleogene
3rd rowNeogene
4th rowPermian
5th rowQuaternary
ValueCountFrequency (%)
paleogene 90464
18.9%
neogene 72075
15.1%
cambrian 48808
10.2%
recent 41336
8.6%
ordovician 34462
 
7.2%
cretaceous 34238
 
7.2%
permian 32455
 
6.8%
quaternary 27798
 
5.8%
devonian 27637
 
5.8%
mississippian 19734
 
4.1%
Other values (14) 49751
10.4%
2025-01-07T11:05:48.219392image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 751141
18.2%
n 506768
12.3%
a 458678
11.1%
i 322536
 
7.8%
o 263741
 
6.4%
r 242986
 
5.9%
g 162539
 
3.9%
s 160613
 
3.9%
P 140533
 
3.4%
c 124669
 
3.0%
Other values (25) 986683
23.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4120887
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 751141
18.2%
n 506768
12.3%
a 458678
11.1%
i 322536
 
7.8%
o 263741
 
6.4%
r 242986
 
5.9%
g 162539
 
3.9%
s 160613
 
3.9%
P 140533
 
3.4%
c 124669
 
3.0%
Other values (25) 986683
23.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4120887
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 751141
18.2%
n 506768
12.3%
a 458678
11.1%
i 322536
 
7.8%
o 263741
 
6.4%
r 242986
 
5.9%
g 162539
 
3.9%
s 160613
 
3.9%
P 140533
 
3.4%
c 124669
 
3.0%
Other values (25) 986683
23.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4120887
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 751141
18.2%
n 506768
12.3%
a 458678
11.1%
i 322536
 
7.8%
o 263741
 
6.4%
r 242986
 
5.9%
g 162539
 
3.9%
s 160613
 
3.9%
P 140533
 
3.4%
c 124669
 
3.0%
Other values (25) 986683
23.9%
Distinct15
Distinct (%)0.2%
Missing718167
Missing (%)99.1%
Memory size5.5 MiB
2025-01-07T11:05:48.274392image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length10
Mean length8.077905693
Min length6

Characters and Unicode

Total characters51222
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowDevonian
2nd rowNeogene
3rd rowCretaceous
4th rowQuaternary
5th rowRecent
ValueCountFrequency (%)
neogene 3161
49.9%
paleogene 1404
22.1%
quaternary 668
 
10.5%
devonian 416
 
6.6%
cretaceous 185
 
2.9%
cambrian 161
 
2.5%
ordovician 137
 
2.2%
pennsylvanian 77
 
1.2%
recent 60
 
0.9%
silurian 30
 
0.5%
Other values (5) 42
 
0.7%
2025-01-07T11:05:48.381730image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 15352
30.0%
n 6768
13.2%
o 5307
 
10.4%
g 4565
 
8.9%
a 4026
 
7.9%
N 3161
 
6.2%
r 1892
 
3.7%
l 1511
 
2.9%
P 1484
 
2.9%
i 1053
 
2.1%
Other values (18) 6103
 
11.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 51222
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 15352
30.0%
n 6768
13.2%
o 5307
 
10.4%
g 4565
 
8.9%
a 4026
 
7.9%
N 3161
 
6.2%
r 1892
 
3.7%
l 1511
 
2.9%
P 1484
 
2.9%
i 1053
 
2.1%
Other values (18) 6103
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 51222
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 15352
30.0%
n 6768
13.2%
o 5307
 
10.4%
g 4565
 
8.9%
a 4026
 
7.9%
N 3161
 
6.2%
r 1892
 
3.7%
l 1511
 
2.9%
P 1484
 
2.9%
i 1053
 
2.1%
Other values (18) 6103
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 51222
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 15352
30.0%
n 6768
13.2%
o 5307
 
10.4%
g 4565
 
8.9%
a 4026
 
7.9%
N 3161
 
6.2%
r 1892
 
3.7%
l 1511
 
2.9%
P 1484
 
2.9%
i 1053
 
2.1%
Other values (18) 6103
 
11.9%
Distinct24
Distinct (%)< 0.1%
Missing376914
Missing (%)52.0%
Memory size5.5 MiB
2025-01-07T11:05:48.436237image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.357434248
Min length1

Characters and Unicode

Total characters2209806
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowMiddle
2nd rowEocene
3rd rowPliocene
4th rowPleistocene
5th rowEarly
ValueCountFrequency (%)
middle 68576
19.7%
eocene 66980
19.3%
late 57993
16.7%
miocene 39410
11.3%
early 37474
10.8%
pliocene 32039
9.2%
pleistocene 20013
 
5.8%
oligocene 15521
 
4.5%
paleocene 7752
 
2.2%
holocene 1481
 
0.4%
Other values (10) 355
 
0.1%
2025-01-07T11:05:48.545398image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 520801
23.6%
o 184703
 
8.4%
n 183525
 
8.3%
c 183200
 
8.3%
l 183151
 
8.3%
i 175926
 
8.0%
d 137364
 
6.2%
M 107985
 
4.9%
E 104453
 
4.7%
a 104017
 
4.7%
Other values (22) 324681
14.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2209806
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 520801
23.6%
o 184703
 
8.4%
n 183525
 
8.3%
c 183200
 
8.3%
l 183151
 
8.3%
i 175926
 
8.0%
d 137364
 
6.2%
M 107985
 
4.9%
E 104453
 
4.7%
a 104017
 
4.7%
Other values (22) 324681
14.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2209806
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 520801
23.6%
o 184703
 
8.4%
n 183525
 
8.3%
c 183200
 
8.3%
l 183151
 
8.3%
i 175926
 
8.0%
d 137364
 
6.2%
M 107985
 
4.9%
E 104453
 
4.7%
a 104017
 
4.7%
Other values (22) 324681
14.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2209806
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 520801
23.6%
o 184703
 
8.4%
n 183525
 
8.3%
c 183200
 
8.3%
l 183151
 
8.3%
i 175926
 
8.0%
d 137364
 
6.2%
M 107985
 
4.9%
E 104453
 
4.7%
a 104017
 
4.7%
Other values (22) 324681
14.7%
Distinct12
Distinct (%)0.2%
Missing718290
Missing (%)99.1%
Memory size5.5 MiB
2025-01-07T11:05:48.596498image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length9
Mean length7.33708588
Min length4

Characters and Unicode

Total characters45622
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowMiddle
2nd rowPliocene
3rd rowLate
4th rowPleistocene
5th rowMiocene
ValueCountFrequency (%)
pliocene 2384
38.3%
eocene 1075
17.3%
miocene 759
 
12.2%
late 645
 
10.4%
pleistocene 645
 
10.4%
middle 364
 
5.9%
oligocene 188
 
3.0%
paleocene 97
 
1.6%
early 34
 
0.5%
holocene 14
 
0.2%
Other values (2) 13
 
0.2%
2025-01-07T11:05:48.785819image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 12099
26.5%
o 5177
11.3%
n 5176
11.3%
c 5174
11.3%
i 4342
 
9.5%
l 3726
 
8.2%
P 3126
 
6.9%
t 1302
 
2.9%
M 1123
 
2.5%
E 1109
 
2.4%
Other values (11) 3268
 
7.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 45622
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 12099
26.5%
o 5177
11.3%
n 5176
11.3%
c 5174
11.3%
i 4342
 
9.5%
l 3726
 
8.2%
P 3126
 
6.9%
t 1302
 
2.9%
M 1123
 
2.5%
E 1109
 
2.4%
Other values (11) 3268
 
7.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 45622
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 12099
26.5%
o 5177
11.3%
n 5176
11.3%
c 5174
11.3%
i 4342
 
9.5%
l 3726
 
8.2%
P 3126
 
6.9%
t 1302
 
2.9%
M 1123
 
2.5%
E 1109
 
2.4%
Other values (11) 3268
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 45622
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 12099
26.5%
o 5177
11.3%
n 5176
11.3%
c 5174
11.3%
i 4342
 
9.5%
l 3726
 
8.2%
P 3126
 
6.9%
t 1302
 
2.9%
M 1123
 
2.5%
E 1109
 
2.4%
Other values (11) 3268
 
7.2%
Distinct366
Distinct (%)0.2%
Missing562472
Missing (%)77.6%
Memory size5.5 MiB
2025-01-07T11:05:48.977396image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length19
Mean length9.036053716
Min length4

Characters and Unicode

Total characters1464166
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)< 0.1%

Sample

1st rowAnisian
2nd rowHemphillian
3rd rowMiddle
4th rowEmsian
5th rowIrvingtonian
ValueCountFrequency (%)
hemphillian 19681
 
12.1%
middle 17380
 
10.7%
wasatchian 7037
 
4.3%
early 5466
 
3.4%
orellan 5085
 
3.1%
bridgerian 4799
 
2.9%
maastrichtian 4686
 
2.9%
campanian 4051
 
2.5%
chadronian 3871
 
2.4%
ypresian 3476
 
2.1%
Other values (350) 87399
53.6%
2025-01-07T11:05:49.246343image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 228885
15.6%
n 195907
13.4%
i 190767
13.0%
e 105142
 
7.2%
l 96307
 
6.6%
r 75689
 
5.2%
d 61340
 
4.2%
o 52724
 
3.6%
h 47497
 
3.2%
s 40454
 
2.8%
Other values (44) 369454
25.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1464166
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 228885
15.6%
n 195907
13.4%
i 190767
13.0%
e 105142
 
7.2%
l 96307
 
6.6%
r 75689
 
5.2%
d 61340
 
4.2%
o 52724
 
3.6%
h 47497
 
3.2%
s 40454
 
2.8%
Other values (44) 369454
25.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1464166
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 228885
15.6%
n 195907
13.4%
i 190767
13.0%
e 105142
 
7.2%
l 96307
 
6.6%
r 75689
 
5.2%
d 61340
 
4.2%
o 52724
 
3.6%
h 47497
 
3.2%
s 40454
 
2.8%
Other values (44) 369454
25.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1464166
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 228885
15.6%
n 195907
13.4%
i 190767
13.0%
e 105142
 
7.2%
l 96307
 
6.6%
r 75689
 
5.2%
d 61340
 
4.2%
o 52724
 
3.6%
h 47497
 
3.2%
s 40454
 
2.8%
Other values (44) 369454
25.2%
Distinct35
Distinct (%)1.5%
Missing722133
Missing (%)99.7%
Memory size5.5 MiB
2025-01-07T11:05:49.329903image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length8
Mean length8.232
Min length4

Characters and Unicode

Total characters19551
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.2%

Sample

1st rowGivetian
2nd rowTuronian
3rd rowGelasian
4th rowGelasian
5th rowGelasian
ValueCountFrequency (%)
lutetian 829
34.9%
zanclean 319
 
13.4%
tortonian 217
 
9.1%
gelasian 200
 
8.4%
maastrichtian 105
 
4.4%
late 98
 
4.1%
thanetian 78
 
3.3%
messinian 78
 
3.3%
ypresian 60
 
2.5%
langhian 58
 
2.4%
Other values (25) 333
14.0%
2025-01-07T11:05:49.450388image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3358
17.2%
n 3107
15.9%
t 2287
11.7%
i 2268
11.6%
e 1838
9.4%
L 1015
 
5.2%
u 862
 
4.4%
l 662
 
3.4%
o 553
 
2.8%
s 534
 
2.7%
Other values (28) 3067
15.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19551
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3358
17.2%
n 3107
15.9%
t 2287
11.7%
i 2268
11.6%
e 1838
9.4%
L 1015
 
5.2%
u 862
 
4.4%
l 662
 
3.4%
o 553
 
2.8%
s 534
 
2.7%
Other values (28) 3067
15.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19551
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3358
17.2%
n 3107
15.9%
t 2287
11.7%
i 2268
11.6%
e 1838
9.4%
L 1015
 
5.2%
u 862
 
4.4%
l 662
 
3.4%
o 553
 
2.8%
s 534
 
2.7%
Other values (28) 3067
15.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19551
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3358
17.2%
n 3107
15.9%
t 2287
11.7%
i 2268
11.6%
e 1838
9.4%
L 1015
 
5.2%
u 862
 
4.4%
l 662
 
3.4%
o 553
 
2.8%
s 534
 
2.7%
Other values (28) 3067
15.7%

lowestBiostratigraphicZone
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

highestBiostratigraphicZone
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

lithostratigraphicTerms
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

group
Text

Missing 

Distinct557
Distinct (%)0.6%
Missing633218
Missing (%)87.4%
Memory size5.5 MiB
2025-01-07T11:05:49.632989image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length28
Mean length14.80891664
Min length1

Characters and Unicode

Total characters1351906
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)0.2%

Sample

1st rowStar Peak Group
2nd rowChesapeake Group
3rd rowKeokuk Group
4th rowChesapeake Group
5th rowChesapeake Group
ValueCountFrequency (%)
group 90331
46.7%
chesapeake 38410
19.9%
river 7802
 
4.0%
white 5751
 
3.0%
selma 3439
 
1.8%
kewanee 2702
 
1.4%
hamilton 2337
 
1.2%
osage 2256
 
1.2%
washita 1421
 
0.7%
pamunkey 1419
 
0.7%
Other values (577) 37508
19.4%
2025-01-07T11:05:49.892397image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 166874
12.3%
p 131366
9.7%
a 118438
 
8.8%
r 115845
 
8.6%
o 113583
 
8.4%
102086
 
7.6%
u 98547
 
7.3%
G 90741
 
6.7%
s 54633
 
4.0%
h 50628
 
3.7%
Other values (47) 309165
22.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1351906
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 166874
12.3%
p 131366
9.7%
a 118438
 
8.8%
r 115845
 
8.6%
o 113583
 
8.4%
102086
 
7.6%
u 98547
 
7.3%
G 90741
 
6.7%
s 54633
 
4.0%
h 50628
 
3.7%
Other values (47) 309165
22.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1351906
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 166874
12.3%
p 131366
9.7%
a 118438
 
8.8%
r 115845
 
8.6%
o 113583
 
8.4%
102086
 
7.6%
u 98547
 
7.3%
G 90741
 
6.7%
s 54633
 
4.0%
h 50628
 
3.7%
Other values (47) 309165
22.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1351906
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 166874
12.3%
p 131366
9.7%
a 118438
 
8.8%
r 115845
 
8.6%
o 113583
 
8.4%
102086
 
7.6%
u 98547
 
7.3%
G 90741
 
6.7%
s 54633
 
4.0%
h 50628
 
3.7%
Other values (47) 309165
22.9%

formation
Text

Missing 

Distinct5419
Distinct (%)1.5%
Missing365706
Missing (%)50.5%
Memory size5.5 MiB
2025-01-07T11:05:50.086745image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length46
Median length38
Mean length11.49027319
Min length3

Characters and Unicode

Total characters4122733
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1482 ?
Unique (%)0.4%

Sample

1st rowPrida Fm
2nd rowYorktown Fm
3rd rowSkinner Ranch Fm
4th rowSan Pedro Fm
5th rowGrande Greve Fm
ValueCountFrequency (%)
fm 259134
32.0%
river 44301
 
5.5%
ls 39737
 
4.9%
stephen 31376
 
3.9%
green 29207
 
3.6%
yorktown 23754
 
2.9%
unknown 18762
 
2.3%
sh 17735
 
2.2%
pungo 10262
 
1.3%
canyon 8111
 
1.0%
Other values (4425) 326422
40.4%
2025-01-07T11:05:50.342255image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
449999
 
10.9%
e 361227
 
8.8%
n 317355
 
7.7%
m 288475
 
7.0%
F 271104
 
6.6%
r 245377
 
6.0%
o 238913
 
5.8%
a 212844
 
5.2%
i 166070
 
4.0%
t 160119
 
3.9%
Other values (56) 1411250
34.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4122733
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
449999
 
10.9%
e 361227
 
8.8%
n 317355
 
7.7%
m 288475
 
7.0%
F 271104
 
6.6%
r 245377
 
6.0%
o 238913
 
5.8%
a 212844
 
5.2%
i 166070
 
4.0%
t 160119
 
3.9%
Other values (56) 1411250
34.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4122733
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
449999
 
10.9%
e 361227
 
8.8%
n 317355
 
7.7%
m 288475
 
7.0%
F 271104
 
6.6%
r 245377
 
6.0%
o 238913
 
5.8%
a 212844
 
5.2%
i 166070
 
4.0%
t 160119
 
3.9%
Other values (56) 1411250
34.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4122733
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
449999
 
10.9%
e 361227
 
8.8%
n 317355
 
7.7%
m 288475
 
7.0%
F 271104
 
6.6%
r 245377
 
6.0%
o 238913
 
5.8%
a 212844
 
5.2%
i 166070
 
4.0%
t 160119
 
3.9%
Other values (56) 1411250
34.2%

member
Text

Missing 

Distinct1626
Distinct (%)2.0%
Missing643191
Missing (%)88.8%
Memory size5.5 MiB
2025-01-07T11:05:50.537901image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length30
Mean length13.99831524
Min length1

Characters and Unicode

Total characters1138301
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique471 ?
Unique (%)0.6%

Sample

1st rowFossil Hill Mbr
2nd rowDecie Ranch Mbr
3rd rowMillersburg Mbr
4th rowThin-Bedded Zone Of Udden
5th rowBurgess Sh Mbr
ValueCountFrequency (%)
mbr 79698
34.1%
sh 36967
15.8%
burgess 30811
 
13.2%
ls 6535
 
2.8%
creek 4230
 
1.8%
meadow 3525
 
1.5%
sunken 3525
 
1.5%
ranch 3361
 
1.4%
francis 2603
 
1.1%
b 2492
 
1.1%
Other values (1500) 60135
25.7%
2025-01-07T11:05:50.793673image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
152565
13.4%
r 138201
12.1%
M 87327
 
7.7%
s 86157
 
7.6%
b 84523
 
7.4%
e 79157
 
7.0%
h 47967
 
4.2%
S 46866
 
4.1%
u 42615
 
3.7%
a 41195
 
3.6%
Other values (60) 331728
29.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1138301
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
152565
13.4%
r 138201
12.1%
M 87327
 
7.7%
s 86157
 
7.6%
b 84523
 
7.4%
e 79157
 
7.0%
h 47967
 
4.2%
S 46866
 
4.1%
u 42615
 
3.7%
a 41195
 
3.6%
Other values (60) 331728
29.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1138301
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
152565
13.4%
r 138201
12.1%
M 87327
 
7.7%
s 86157
 
7.6%
b 84523
 
7.4%
e 79157
 
7.0%
h 47967
 
4.2%
S 46866
 
4.1%
u 42615
 
3.7%
a 41195
 
3.6%
Other values (60) 331728
29.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1138301
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
152565
13.4%
r 138201
12.1%
M 87327
 
7.7%
s 86157
 
7.6%
b 84523
 
7.4%
e 79157
 
7.0%
h 47967
 
4.2%
S 46866
 
4.1%
u 42615
 
3.7%
a 41195
 
3.6%
Other values (60) 331728
29.1%

bed
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

identificationID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

verbatimIdentification
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

identificationQualifier
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

typeStatus
Text

Missing 

Distinct15
Distinct (%)< 0.1%
Missing582086
Missing (%)80.3%
Memory size5.5 MiB
2025-01-07T11:05:50.855814image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length8
Mean length7.803239668
Min length4

Characters and Unicode

Total characters1111353
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPARATYPE
2nd rowPARATYPE
3rd rowPARATYPE
4th rowTYPE
5th rowHOLOTYPE
ValueCountFrequency (%)
paratype 74612
52.4%
holotype 34645
24.3%
syntype 19534
 
13.7%
type 7903
 
5.5%
paralectotype 2966
 
2.1%
lectotype 1051
 
0.7%
plastoholotype 593
 
0.4%
plastotype 389
 
0.3%
plastoparatype 282
 
0.2%
plastosyntype 253
 
0.2%
Other values (5) 194
 
0.1%
2025-01-07T11:05:50.961960image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 221818
20.0%
Y 162209
14.6%
A 157256
14.1%
T 147992
13.3%
E 146600
13.2%
R 77860
 
7.0%
O 76223
 
6.9%
L 40808
 
3.7%
H 35238
 
3.2%
S 21351
 
1.9%
Other values (3) 23998
 
2.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1111353
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
P 221818
20.0%
Y 162209
14.6%
A 157256
14.1%
T 147992
13.3%
E 146600
13.2%
R 77860
 
7.0%
O 76223
 
6.9%
L 40808
 
3.7%
H 35238
 
3.2%
S 21351
 
1.9%
Other values (3) 23998
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1111353
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
P 221818
20.0%
Y 162209
14.6%
A 157256
14.1%
T 147992
13.3%
E 146600
13.2%
R 77860
 
7.0%
O 76223
 
6.9%
L 40808
 
3.7%
H 35238
 
3.2%
S 21351
 
1.9%
Other values (3) 23998
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1111353
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
P 221818
20.0%
Y 162209
14.6%
A 157256
14.1%
T 147992
13.3%
E 146600
13.2%
R 77860
 
7.0%
O 76223
 
6.9%
L 40808
 
3.7%
H 35238
 
3.2%
S 21351
 
1.9%
Other values (3) 23998
 
2.2%

identifiedBy
Text

Missing 

Distinct2463
Distinct (%)1.2%
Missing521981
Missing (%)72.0%
Memory size5.5 MiB
2025-01-07T11:05:51.150476image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length147
Median length124
Mean length22.47668212
Min length2

Characters and Unicode

Total characters4552135
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique535 ?
Unique (%)0.3%

Sample

1st rowSilberling; Nichols
2nd rowVaughan
3rd rowHarper; Boucot
4th rowSaid; Barakat, M. G.
5th rowSmith
ValueCountFrequency (%)
united 21468
 
3.2%
states 21082
 
3.2%
of 20281
 
3.1%
museum 15734
 
2.4%
helen 15316
 
2.3%
12006
 
1.8%
natural 11887
 
1.8%
history 11620
 
1.8%
institution 11572
 
1.7%
smithsonian 11571
 
1.7%
Other values (2466) 510240
77.0%
2025-01-07T11:05:51.431266image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
460250
 
10.1%
e 280098
 
6.2%
o 272102
 
6.0%
a 259642
 
5.7%
n 241275
 
5.3%
t 230888
 
5.1%
r 226036
 
5.0%
i 214007
 
4.7%
l 181066
 
4.0%
s 174306
 
3.8%
Other values (58) 2012465
44.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4552135
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
460250
 
10.1%
e 280098
 
6.2%
o 272102
 
6.0%
a 259642
 
5.7%
n 241275
 
5.3%
t 230888
 
5.1%
r 226036
 
5.0%
i 214007
 
4.7%
l 181066
 
4.0%
s 174306
 
3.8%
Other values (58) 2012465
44.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4552135
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
460250
 
10.1%
e 280098
 
6.2%
o 272102
 
6.0%
a 259642
 
5.7%
n 241275
 
5.3%
t 230888
 
5.1%
r 226036
 
5.0%
i 214007
 
4.7%
l 181066
 
4.0%
s 174306
 
3.8%
Other values (58) 2012465
44.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4552135
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
460250
 
10.1%
e 280098
 
6.2%
o 272102
 
6.0%
a 259642
 
5.7%
n 241275
 
5.3%
t 230888
 
5.1%
r 226036
 
5.0%
i 214007
 
4.7%
l 181066
 
4.0%
s 174306
 
3.8%
Other values (58) 2012465
44.2%

identifiedByID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

dateIdentified
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

identificationReferences
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

identificationVerificationStatus
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

identificationRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

taxonID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

scientificNameID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

acceptedNameUsageID
Real number (ℝ)

Missing 

Distinct58335
Distinct (%)10.6%
Missing171789
Missing (%)23.7%
Infinite0
Infinite (%)0.0%
Mean5515085.25
Minimum1
Maximum12385426
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:51.509432image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile216
Q13249393
median4941659
Q38513230
95-th percentile9626241
Maximum12385426
Range12385425
Interquartile range (IQR)5263837

Descriptive statistics

Standard deviation3184869.125
Coefficient of variation (CV)0.5774832084
Kurtosis-0.8885403732
Mean5515085.25
Median Absolute Deviation (MAD)2688948
Skewness-0.1769613565
Sum3.048292404 × 1012
Variance1.014339134 × 1013
MonotonicityNot monotonic
2025-01-07T11:05:51.577431image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
216 16872
 
2.3%
8513230 13693
 
1.9%
4806028 12281
 
1.7%
6 11457
 
1.6%
359 4656
 
0.6%
44 4268
 
0.6%
729 3674
 
0.5%
353 3566
 
0.5%
2481460 3232
 
0.4%
4832444 3022
 
0.4%
Other values (58325) 475998
65.7%
(Missing) 171789
 
23.7%
ValueCountFrequency (%)
1 1114
 
0.2%
6 11457
1.6%
42 952
 
0.1%
43 51
 
< 0.1%
44 4268
 
0.6%
ValueCountFrequency (%)
12385426 4
 
< 0.1%
12385220 2
 
< 0.1%
12379591 6
 
< 0.1%
12362277 15
< 0.1%
12358726 5
 
< 0.1%

parentNameUsageID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

originalNameUsageID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

nameAccordingToID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

namePublishedInID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

taxonConceptID
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB
Distinct65364
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:51.773531image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length124
Median length82
Mean length24.76860849
Min length3

Characters and Unicode

Total characters17945055
Distinct characters109
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24744 ?
Unique (%)3.4%

Sample

1st rowincertae sedis
2nd rowDamaliscus lunatus (Burchell, 1823)
3rd rowAcrochordiceras hyatti Meek, 1877
4th rowDiscocyclina sculpturata (Cushman, 1919)
5th rowOdontaspis cuspidata (Agassiz, 1843)
ValueCountFrequency (%)
incertae 171789
 
7.4%
sedis 171789
 
7.4%
80645
 
3.5%
walcott 31003
 
1.3%
cooper 24261
 
1.1%
cushman 17003
 
0.7%
insecta 16882
 
0.7%
1912 16564
 
0.7%
grant 16169
 
0.7%
1976 14713
 
0.6%
Other values (47365) 1749493
75.7%
2025-01-07T11:05:52.056806image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1585803
 
8.8%
e 1485632
 
8.3%
a 1415466
 
7.9%
i 1243670
 
6.9%
s 1115918
 
6.2%
r 978896
 
5.5%
n 888307
 
5.0%
o 817782
 
4.6%
t 774995
 
4.3%
l 698421
 
3.9%
Other values (99) 6940165
38.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17945055
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1585803
 
8.8%
e 1485632
 
8.3%
a 1415466
 
7.9%
i 1243670
 
6.9%
s 1115918
 
6.2%
r 978896
 
5.5%
n 888307
 
5.0%
o 817782
 
4.6%
t 774995
 
4.3%
l 698421
 
3.9%
Other values (99) 6940165
38.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17945055
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1585803
 
8.8%
e 1485632
 
8.3%
a 1415466
 
7.9%
i 1243670
 
6.9%
s 1115918
 
6.2%
r 978896
 
5.5%
n 888307
 
5.0%
o 817782
 
4.6%
t 774995
 
4.3%
l 698421
 
3.9%
Other values (99) 6940165
38.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17945055
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1585803
 
8.8%
e 1485632
 
8.3%
a 1415466
 
7.9%
i 1243670
 
6.9%
s 1115918
 
6.2%
r 978896
 
5.5%
n 888307
 
5.0%
o 817782
 
4.6%
t 774995
 
4.3%
l 698421
 
3.9%
Other values (99) 6940165
38.7%

acceptedNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

parentNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

originalNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

nameAccordingTo
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

namePublishedIn
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

namePublishedInYear
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

higherClassification
Text

Missing 

Distinct3844
Distinct (%)0.7%
Missing172643
Missing (%)23.8%
Memory size5.5 MiB
2025-01-07T11:05:52.211072image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length141
Median length123
Mean length59.08444638
Min length5

Characters and Unicode

Total characters32606638
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique743 ?
Unique (%)0.1%

Sample

1st rowAnimalia, Chordata, Vertebrata, Mammalia, Eutheria, Laurasiatheria, Artiodactyla, Ruminatia, Bovidae
2nd rowAnimalia, Mollusca, Cephalopoda, Ammonoidea
3rd rowChromista, Foraminifera, Globothalamea, Rotaliida, Discocyclinidae
4th rowAnimalia, Chordata, Vertebrata, Pisces, Chondrichthyes, Elasmobranchii, Galeomorphii, Lamniformes, Odontaspididae
5th rowAnimalia, Brachiopoda, Rhynchonellata, Orthida, Enteletidae
ValueCountFrequency (%)
animalia 448323
 
15.7%
chordata 148700
 
5.2%
vertebrata 148618
 
5.2%
arthropoda 100318
 
3.5%
mollusca 69025
 
2.4%
brachiopoda 66748
 
2.3%
foraminifera 66301
 
2.3%
chromista 65999
 
2.3%
mammalia 60027
 
2.1%
eutheria 57586
 
2.0%
Other values (3834) 1620986
56.8%
2025-01-07T11:05:52.440873image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4706865
14.4%
i 3184420
 
9.8%
2300766
 
7.1%
, 2260526
 
6.9%
o 2052009
 
6.3%
r 2005114
 
6.1%
e 1809015
 
5.5%
t 1671086
 
5.1%
l 1501858
 
4.6%
n 1400746
 
4.3%
Other values (51) 9714233
29.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 32606638
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4706865
14.4%
i 3184420
 
9.8%
2300766
 
7.1%
, 2260526
 
6.9%
o 2052009
 
6.3%
r 2005114
 
6.1%
e 1809015
 
5.5%
t 1671086
 
5.1%
l 1501858
 
4.6%
n 1400746
 
4.3%
Other values (51) 9714233
29.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 32606638
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4706865
14.4%
i 3184420
 
9.8%
2300766
 
7.1%
, 2260526
 
6.9%
o 2052009
 
6.3%
r 2005114
 
6.1%
e 1809015
 
5.5%
t 1671086
 
5.1%
l 1501858
 
4.6%
n 1400746
 
4.3%
Other values (51) 9714233
29.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 32606638
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4706865
14.4%
i 3184420
 
9.8%
2300766
 
7.1%
, 2260526
 
6.9%
o 2052009
 
6.3%
r 2005114
 
6.1%
e 1809015
 
5.5%
t 1671086
 
5.1%
l 1501858
 
4.6%
n 1400746
 
4.3%
Other values (51) 9714233
29.8%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:52.499880image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length8
Mean length9.46887543
Min length5

Characters and Unicode

Total characters6860276
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowincertae sedis
2nd rowAnimalia
3rd rowAnimalia
4th rowChromista
5th rowAnimalia
ValueCountFrequency (%)
animalia 446288
49.8%
incertae 171929
 
19.2%
sedis 171929
 
19.2%
chromista 69124
 
7.7%
plantae 36324
 
4.1%
bacteria 502
 
0.1%
protozoa 287
 
< 0.1%
fungi 54
 
< 0.1%
2025-01-07T11:05:52.689268image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1306114
19.0%
a 1207568
17.6%
n 654595
9.5%
e 552613
8.1%
m 515412
 
7.5%
l 482612
 
7.0%
A 446288
 
6.5%
s 412982
 
6.0%
t 278166
 
4.1%
r 241842
 
3.5%
Other values (12) 762084
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6860276
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 1306114
19.0%
a 1207568
17.6%
n 654595
9.5%
e 552613
8.1%
m 515412
 
7.5%
l 482612
 
7.0%
A 446288
 
6.5%
s 412982
 
6.0%
t 278166
 
4.1%
r 241842
 
3.5%
Other values (12) 762084
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6860276
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 1306114
19.0%
a 1207568
17.6%
n 654595
9.5%
e 552613
8.1%
m 515412
 
7.5%
l 482612
 
7.0%
A 446288
 
6.5%
s 412982
 
6.0%
t 278166
 
4.1%
r 241842
 
3.5%
Other values (12) 762084
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6860276
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 1306114
19.0%
a 1207568
17.6%
n 654595
9.5%
e 552613
8.1%
m 515412
 
7.5%
l 482612
 
7.0%
A 446288
 
6.5%
s 412982
 
6.0%
t 278166
 
4.1%
r 241842
 
3.5%
Other values (12) 762084
11.1%

phylum
Text

Missing 

Distinct40
Distinct (%)< 0.1%
Missing192842
Missing (%)26.6%
Memory size5.5 MiB
2025-01-07T11:05:52.752777image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length16
Mean length9.682191451
Min length7

Characters and Unicode

Total characters5147692
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowChordata
2nd rowMollusca
3rd rowForaminifera
4th rowChordata
5th rowBrachiopoda
ValueCountFrequency (%)
chordata 148527
27.9%
arthropoda 101505
19.1%
mollusca 66708
12.5%
foraminifera 66099
12.4%
brachiopoda 65633
12.3%
echinodermata 27100
 
5.1%
tracheophyta 21340
 
4.0%
bryozoa 13677
 
2.6%
cnidaria 6914
 
1.3%
annelida 3027
 
0.6%
Other values (30) 11136
 
2.1%
2025-01-07T11:05:52.866654image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 872631
17.0%
o 702054
13.6%
r 631416
12.3%
h 394973
 
7.7%
d 356870
 
6.9%
t 305449
 
5.9%
i 250365
 
4.9%
p 194047
 
3.8%
c 186323
 
3.6%
C 156569
 
3.0%
Other values (25) 1096995
21.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5147692
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 872631
17.0%
o 702054
13.6%
r 631416
12.3%
h 394973
 
7.7%
d 356870
 
6.9%
t 305449
 
5.9%
i 250365
 
4.9%
p 194047
 
3.8%
c 186323
 
3.6%
C 156569
 
3.0%
Other values (25) 1096995
21.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5147692
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 872631
17.0%
o 702054
13.6%
r 631416
12.3%
h 394973
 
7.7%
d 356870
 
6.9%
t 305449
 
5.9%
i 250365
 
4.9%
p 194047
 
3.8%
c 186323
 
3.6%
C 156569
 
3.0%
Other values (25) 1096995
21.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5147692
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 872631
17.0%
o 702054
13.6%
r 631416
12.3%
h 394973
 
7.7%
d 356870
 
6.9%
t 305449
 
5.9%
i 250365
 
4.9%
p 194047
 
3.8%
c 186323
 
3.6%
C 156569
 
3.0%
Other values (25) 1096995
21.3%

class
Text

Missing 

Distinct92
Distinct (%)< 0.1%
Missing272566
Missing (%)37.6%
Memory size5.5 MiB
2025-01-07T11:05:52.966166image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.989064969
Min length4

Characters and Unicode

Total characters4514478
Distinct characters42
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowMammalia
2nd rowCephalopoda
3rd rowGlobothalamea
4th rowElasmobranchii
5th rowRhynchonellata
ValueCountFrequency (%)
mammalia 59795
13.2%
globothalamea 42882
 
9.5%
rhynchonellata 39551
 
8.8%
aves 34584
 
7.7%
insecta 32733
 
7.2%
gastropoda 24245
 
5.4%
ostracoda 23481
 
5.2%
elasmobranchii 23303
 
5.2%
trilobita 22315
 
4.9%
bivalvia 22257
 
4.9%
Other values (82) 126796
28.1%
2025-01-07T11:05:53.124011image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 873045
19.3%
o 420982
 
9.3%
l 396601
 
8.8%
i 316058
 
7.0%
t 241147
 
5.3%
e 235006
 
5.2%
m 212254
 
4.7%
n 206140
 
4.6%
h 195566
 
4.3%
s 167736
 
3.7%
Other values (32) 1249943
27.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4514478
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 873045
19.3%
o 420982
 
9.3%
l 396601
 
8.8%
i 316058
 
7.0%
t 241147
 
5.3%
e 235006
 
5.2%
m 212254
 
4.7%
n 206140
 
4.6%
h 195566
 
4.3%
s 167736
 
3.7%
Other values (32) 1249943
27.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4514478
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 873045
19.3%
o 420982
 
9.3%
l 396601
 
8.8%
i 316058
 
7.0%
t 241147
 
5.3%
e 235006
 
5.2%
m 212254
 
4.7%
n 206140
 
4.6%
h 195566
 
4.3%
s 167736
 
3.7%
Other values (32) 1249943
27.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4514478
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 873045
19.3%
o 420982
 
9.3%
l 396601
 
8.8%
i 316058
 
7.0%
t 241147
 
5.3%
e 235006
 
5.2%
m 212254
 
4.7%
n 206140
 
4.6%
h 195566
 
4.3%
s 167736
 
3.7%
Other values (32) 1249943
27.7%

order
Text

Missing 

Distinct484
Distinct (%)0.1%
Missing369296
Missing (%)51.0%
Memory size5.5 MiB
2025-01-07T11:05:53.252799image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length17
Mean length11.06623369
Min length5

Characters and Unicode

Total characters3930859
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)< 0.1%

Sample

1st rowArtiodactyla
2nd rowCeratitida
3rd rowRotaliida
4th rowLamniformes
5th rowProcellariiformes
ValueCountFrequency (%)
rotaliida 32460
 
9.1%
diptera 14185
 
4.0%
porocephalida 14086
 
4.0%
podocopida 12424
 
3.5%
lamniformes 11376
 
3.2%
cetacea 10382
 
2.9%
procellariiformes 9895
 
2.8%
artiodactyla 8981
 
2.5%
terebratulida 8715
 
2.5%
perissodactyla 7870
 
2.2%
Other values (474) 224838
63.3%
2025-01-07T11:05:53.452298image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 543173
13.8%
i 471633
12.0%
o 372619
 
9.5%
r 281531
 
7.2%
e 276408
 
7.0%
d 260645
 
6.6%
t 210238
 
5.3%
l 209185
 
5.3%
s 166314
 
4.2%
c 134203
 
3.4%
Other values (40) 1004910
25.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3930859
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 543173
13.8%
i 471633
12.0%
o 372619
 
9.5%
r 281531
 
7.2%
e 276408
 
7.0%
d 260645
 
6.6%
t 210238
 
5.3%
l 209185
 
5.3%
s 166314
 
4.2%
c 134203
 
3.4%
Other values (40) 1004910
25.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3930859
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 543173
13.8%
i 471633
12.0%
o 372619
 
9.5%
r 281531
 
7.2%
e 276408
 
7.0%
d 260645
 
6.6%
t 210238
 
5.3%
l 209185
 
5.3%
s 166314
 
4.2%
c 134203
 
3.4%
Other values (40) 1004910
25.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3930859
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 543173
13.8%
i 471633
12.0%
o 372619
 
9.5%
r 281531
 
7.2%
e 276408
 
7.0%
d 260645
 
6.6%
t 210238
 
5.3%
l 209185
 
5.3%
s 166314
 
4.2%
c 134203
 
3.4%
Other values (40) 1004910
25.6%

superfamily
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

family
Text

Missing 

Distinct4830
Distinct (%)1.0%
Missing258765
Missing (%)35.7%
Memory size5.5 MiB
2025-01-07T11:05:53.616208image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length21
Mean length12.53716749
Min length5

Characters and Unicode

Total characters5839098
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique637 ?
Unique (%)0.1%

Sample

1st rowBovidae
2nd rowAcrochordiceratidae
3rd rowOrbitoclypeidae
4th rowOdontaspididae
5th rowEnteletidae
ValueCountFrequency (%)
subtriquetridae 14086
 
3.0%
milichiidae 13693
 
2.9%
procellariidae 9409
 
2.0%
lamnidae 7013
 
1.5%
carcharhinidae 5646
 
1.2%
anatidae 5251
 
1.1%
phocidae 4763
 
1.0%
vaginulinidae 3864
 
0.8%
equidae 3840
 
0.8%
physeteridae 3794
 
0.8%
Other values (4820) 394384
84.7%
2025-01-07T11:05:53.854484image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 849890
14.6%
e 786222
13.5%
a 738375
12.6%
d 534378
9.2%
r 330492
 
5.7%
o 326737
 
5.6%
l 281417
 
4.8%
t 274019
 
4.7%
n 228653
 
3.9%
c 216586
 
3.7%
Other values (42) 1272329
21.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5839098
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 849890
14.6%
e 786222
13.5%
a 738375
12.6%
d 534378
9.2%
r 330492
 
5.7%
o 326737
 
5.6%
l 281417
 
4.8%
t 274019
 
4.7%
n 228653
 
3.9%
c 216586
 
3.7%
Other values (42) 1272329
21.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5839098
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 849890
14.6%
e 786222
13.5%
a 738375
12.6%
d 534378
9.2%
r 330492
 
5.7%
o 326737
 
5.6%
l 281417
 
4.8%
t 274019
 
4.7%
n 228653
 
3.9%
c 216586
 
3.7%
Other values (42) 1272329
21.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5839098
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 849890
14.6%
e 786222
13.5%
a 738375
12.6%
d 534378
9.2%
r 330492
 
5.7%
o 326737
 
5.6%
l 281417
 
4.8%
t 274019
 
4.7%
n 228653
 
3.9%
c 216586
 
3.7%
Other values (42) 1272329
21.8%

subfamily
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

tribe
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

subtribe
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

genus
Text

Missing 

Distinct20048
Distinct (%)4.2%
Missing245070
Missing (%)33.8%
Memory size5.5 MiB
2025-01-07T11:05:54.057535image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length20
Mean length10.1276432
Min length3

Characters and Unicode

Total characters4855577
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4473 ?
Unique (%)0.9%

Sample

1st rowDamaliscus
2nd rowAcrochordiceras
3rd rowAsterocyclina
4th rowCarcharias
5th rowEnteletes
ValueCountFrequency (%)
genus 13850
 
2.9%
marrella 12281
 
2.6%
pterodroma 6789
 
1.4%
callophoca 3770
 
0.8%
physeterula 3029
 
0.6%
carcharhinus 2974
 
0.6%
australca 2250
 
0.5%
thambetochen 2208
 
0.5%
hustedia 2080
 
0.4%
branta 2051
 
0.4%
Other values (20038) 428156
89.3%
2025-01-07T11:05:54.322082image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 524027
 
10.8%
i 409959
 
8.4%
o 399283
 
8.2%
e 377679
 
7.8%
r 355924
 
7.3%
s 324654
 
6.7%
l 308448
 
6.4%
n 254099
 
5.2%
t 240655
 
5.0%
u 219806
 
4.5%
Other values (43) 1441043
29.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4855577
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 524027
 
10.8%
i 409959
 
8.4%
o 399283
 
8.2%
e 377679
 
7.8%
r 355924
 
7.3%
s 324654
 
6.7%
l 308448
 
6.4%
n 254099
 
5.2%
t 240655
 
5.0%
u 219806
 
4.5%
Other values (43) 1441043
29.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4855577
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 524027
 
10.8%
i 409959
 
8.4%
o 399283
 
8.2%
e 377679
 
7.8%
r 355924
 
7.3%
s 324654
 
6.7%
l 308448
 
6.4%
n 254099
 
5.2%
t 240655
 
5.0%
u 219806
 
4.5%
Other values (43) 1441043
29.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4855577
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 524027
 
10.8%
i 409959
 
8.4%
o 399283
 
8.2%
e 377679
 
7.8%
r 355924
 
7.3%
s 324654
 
6.7%
l 308448
 
6.4%
n 254099
 
5.2%
t 240655
 
5.0%
u 219806
 
4.5%
Other values (43) 1441043
29.7%

genericName
Text

Missing 

Distinct19254
Distinct (%)4.0%
Missing244897
Missing (%)33.8%
Memory size5.5 MiB
2025-01-07T11:05:54.532183image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length19
Mean length10.00970995
Min length3

Characters and Unicode

Total characters4800767
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4453 ?
Unique (%)0.9%

Sample

1st rowDamaliscus
2nd rowAcrochordiceras
3rd rowDiscocyclina
4th rowOdontaspis
5th rowEnteletes
ValueCountFrequency (%)
genus 13850
 
2.9%
marrella 12281
 
2.6%
pterodroma 7305
 
1.5%
callophoca 3770
 
0.8%
isurus 3463
 
0.7%
physeterula 3029
 
0.6%
carcharhinus 2930
 
0.6%
australca 2250
 
0.5%
thambetochen 2208
 
0.5%
hustedia 2082
 
0.4%
Other values (19244) 426443
88.9%
2025-01-07T11:05:54.809952image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 519031
 
10.8%
i 403892
 
8.4%
o 387257
 
8.1%
e 374510
 
7.8%
r 356780
 
7.4%
s 320239
 
6.7%
l 307792
 
6.4%
n 251588
 
5.2%
t 236485
 
4.9%
u 219057
 
4.6%
Other values (45) 1424136
29.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4800767
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 519031
 
10.8%
i 403892
 
8.4%
o 387257
 
8.1%
e 374510
 
7.8%
r 356780
 
7.4%
s 320239
 
6.7%
l 307792
 
6.4%
n 251588
 
5.2%
t 236485
 
4.9%
u 219057
 
4.6%
Other values (45) 1424136
29.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4800767
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 519031
 
10.8%
i 403892
 
8.4%
o 387257
 
8.1%
e 374510
 
7.8%
r 356780
 
7.4%
s 320239
 
6.7%
l 307792
 
6.4%
n 251588
 
5.2%
t 236485
 
4.9%
u 219057
 
4.6%
Other values (45) 1424136
29.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4800767
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 519031
 
10.8%
i 403892
 
8.4%
o 387257
 
8.1%
e 374510
 
7.8%
r 356780
 
7.4%
s 320239
 
6.7%
l 307792
 
6.4%
n 251588
 
5.2%
t 236485
 
4.9%
u 219057
 
4.6%
Other values (45) 1424136
29.7%

subgenus
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

infragenericEpithet
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

specificEpithet
Text

Missing 

Distinct21987
Distinct (%)8.0%
Missing449718
Missing (%)62.1%
Memory size5.5 MiB
2025-01-07T11:05:55.019132image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length17
Mean length8.738418429
Min length2

Characters and Unicode

Total characters2401230
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6275 ?
Unique (%)2.3%

Sample

1st rowlunatus
2nd rowhyatti
3rd rowsculpturata
4th rowcuspidata
5th rowrotundobesus
ValueCountFrequency (%)
phaeopygia 3232
 
1.2%
alba 2027
 
0.7%
megalodon 1648
 
0.6%
confluens 1438
 
0.5%
obscura 1243
 
0.5%
cahow 1050
 
0.4%
hastalis 917
 
0.3%
socialis 884
 
0.3%
varians 883
 
0.3%
paulus 879
 
0.3%
Other values (21977) 260589
94.8%
2025-01-07T11:05:55.280209image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 304358
12.7%
i 265754
11.1%
s 232914
9.7%
e 187242
 
7.8%
n 166271
 
6.9%
r 155825
 
6.5%
u 136921
 
5.7%
o 136782
 
5.7%
l 131891
 
5.5%
t 131533
 
5.5%
Other values (19) 551739
23.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2401230
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 304358
12.7%
i 265754
11.1%
s 232914
9.7%
e 187242
 
7.8%
n 166271
 
6.9%
r 155825
 
6.5%
u 136921
 
5.7%
o 136782
 
5.7%
l 131891
 
5.5%
t 131533
 
5.5%
Other values (19) 551739
23.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2401230
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 304358
12.7%
i 265754
11.1%
s 232914
9.7%
e 187242
 
7.8%
n 166271
 
6.9%
r 155825
 
6.5%
u 136921
 
5.7%
o 136782
 
5.7%
l 131891
 
5.5%
t 131533
 
5.5%
Other values (19) 551739
23.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2401230
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 304358
12.7%
i 265754
11.1%
s 232914
9.7%
e 187242
 
7.8%
n 166271
 
6.9%
r 155825
 
6.5%
u 136921
 
5.7%
o 136782
 
5.7%
l 131891
 
5.5%
t 131533
 
5.5%
Other values (19) 551739
23.0%

infraspecificEpithet
Text

Missing 

Distinct1469
Distinct (%)23.3%
Missing718207
Missing (%)99.1%
Memory size5.5 MiB
2025-01-07T11:05:55.473194image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.022536105
Min length2

Characters and Unicode

Total characters56851
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique540 ?
Unique (%)8.6%

Sample

1st rowcooperensis
2nd rowsubdecorata
3rd rowadvena
4th rowconvexa
5th rowpoloumera
ValueCountFrequency (%)
burchellii 494
 
7.8%
antarctica 104
 
1.7%
inflata 67
 
1.1%
vancouveriensis 64
 
1.0%
mexicana 54
 
0.9%
ornata 50
 
0.8%
caurina 42
 
0.7%
erectus 39
 
0.6%
texana 33
 
0.5%
occidentalis 32
 
0.5%
Other values (1459) 5322
84.5%
2025-01-07T11:05:55.734175image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 8251
14.5%
i 6485
11.4%
s 4930
8.7%
e 4526
 
8.0%
n 4069
 
7.2%
t 3680
 
6.5%
r 3677
 
6.5%
l 3463
 
6.1%
c 3093
 
5.4%
u 2924
 
5.1%
Other values (16) 11753
20.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 56851
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 8251
14.5%
i 6485
11.4%
s 4930
8.7%
e 4526
 
8.0%
n 4069
 
7.2%
t 3680
 
6.5%
r 3677
 
6.5%
l 3463
 
6.1%
c 3093
 
5.4%
u 2924
 
5.1%
Other values (16) 11753
20.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 56851
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 8251
14.5%
i 6485
11.4%
s 4930
8.7%
e 4526
 
8.0%
n 4069
 
7.2%
t 3680
 
6.5%
r 3677
 
6.5%
l 3463
 
6.1%
c 3093
 
5.4%
u 2924
 
5.1%
Other values (16) 11753
20.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 56851
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 8251
14.5%
i 6485
11.4%
s 4930
8.7%
e 4526
 
8.0%
n 4069
 
7.2%
t 3680
 
6.5%
r 3677
 
6.5%
l 3463
 
6.1%
c 3093
 
5.4%
u 2924
 
5.1%
Other values (16) 11753
20.7%

cultivarEpithet
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB
Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:55.796765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length7
Mean length6.306741955
Min length4

Characters and Unicode

Total characters4569285
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKINGDOM
2nd rowSPECIES
3rd rowSPECIES
4th rowSPECIES
5th rowSPECIES
ValueCountFrequency (%)
species 268489
37.1%
genus 204821
28.3%
kingdom 184360
25.4%
class 34827
 
4.8%
family 11500
 
1.6%
order 7792
 
1.1%
phylum 6418
 
0.9%
subspecies 3525
 
0.5%
variety 2760
 
0.4%
form 16
 
< 0.1%
2025-01-07T11:05:55.903510image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 822028
18.0%
E 759401
16.6%
I 470634
10.3%
N 389181
8.5%
G 389181
8.5%
C 306841
 
6.7%
P 278432
 
6.1%
U 214764
 
4.7%
M 202294
 
4.4%
O 192168
 
4.2%
Other values (11) 544361
11.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4569285
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 822028
18.0%
E 759401
16.6%
I 470634
10.3%
N 389181
8.5%
G 389181
8.5%
C 306841
 
6.7%
P 278432
 
6.1%
U 214764
 
4.7%
M 202294
 
4.4%
O 192168
 
4.2%
Other values (11) 544361
11.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4569285
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 822028
18.0%
E 759401
16.6%
I 470634
10.3%
N 389181
8.5%
G 389181
8.5%
C 306841
 
6.7%
P 278432
 
6.1%
U 214764
 
4.7%
M 202294
 
4.4%
O 192168
 
4.2%
Other values (11) 544361
11.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4569285
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 822028
18.0%
E 759401
16.6%
I 470634
10.3%
N 389181
8.5%
G 389181
8.5%
C 306841
 
6.7%
P 278432
 
6.1%
U 214764
 
4.7%
M 202294
 
4.4%
O 192168
 
4.2%
Other values (11) 544361
11.9%

verbatimTaxonRank
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

vernacularName
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

nomenclaturalCode
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

taxonomicStatus
Text

Missing 

Distinct3
Distinct (%)< 0.1%
Missing171789
Missing (%)23.7%
Memory size5.5 MiB
2025-01-07T11:05:55.951015image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.856598018
Min length7

Characters and Unicode

Total characters4342491
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowACCEPTED
2nd rowACCEPTED
3rd rowSYNONYM
4th rowSYNONYM
5th rowACCEPTED
ValueCountFrequency (%)
accepted 431194
78.0%
synonym 79261
 
14.3%
doubtful 42264
 
7.6%
2025-01-07T11:05:56.052269image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 862388
19.9%
E 862388
19.9%
T 473458
10.9%
D 473458
10.9%
A 431194
9.9%
P 431194
9.9%
Y 158522
 
3.7%
N 158522
 
3.7%
O 121525
 
2.8%
U 84528
 
1.9%
Other values (5) 285314
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4342491
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 862388
19.9%
E 862388
19.9%
T 473458
10.9%
D 473458
10.9%
A 431194
9.9%
P 431194
9.9%
Y 158522
 
3.7%
N 158522
 
3.7%
O 121525
 
2.8%
U 84528
 
1.9%
Other values (5) 285314
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4342491
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 862388
19.9%
E 862388
19.9%
T 473458
10.9%
D 473458
10.9%
A 431194
9.9%
P 431194
9.9%
Y 158522
 
3.7%
N 158522
 
3.7%
O 121525
 
2.8%
U 84528
 
1.9%
Other values (5) 285314
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4342491
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 862388
19.9%
E 862388
19.9%
T 473458
10.9%
D 473458
10.9%
A 431194
9.9%
P 431194
9.9%
Y 158522
 
3.7%
N 158522
 
3.7%
O 121525
 
2.8%
U 84528
 
1.9%
Other values (5) 285314
 
6.6%

nomenclaturalStatus
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

taxonRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

datasetKey
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:56.109210image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters26082288
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowc8681cc2-9d0a-4c5f-b620-5c753abfe2bc
2nd rowc8681cc2-9d0a-4c5f-b620-5c753abfe2bc
3rd rowc8681cc2-9d0a-4c5f-b620-5c753abfe2bc
4th rowc8681cc2-9d0a-4c5f-b620-5c753abfe2bc
5th rowc8681cc2-9d0a-4c5f-b620-5c753abfe2bc
ValueCountFrequency (%)
c8681cc2-9d0a-4c5f-b620-5c753abfe2bc 724508
100.0%
2025-01-07T11:05:56.213250image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 4347048
16.7%
- 2898032
11.1%
2 2173524
8.3%
b 2173524
8.3%
5 2173524
8.3%
0 1449016
 
5.6%
f 1449016
 
5.6%
6 1449016
 
5.6%
8 1449016
 
5.6%
a 1449016
 
5.6%
Other values (7) 5071556
19.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26082288
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 4347048
16.7%
- 2898032
11.1%
2 2173524
8.3%
b 2173524
8.3%
5 2173524
8.3%
0 1449016
 
5.6%
f 1449016
 
5.6%
6 1449016
 
5.6%
8 1449016
 
5.6%
a 1449016
 
5.6%
Other values (7) 5071556
19.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26082288
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 4347048
16.7%
- 2898032
11.1%
2 2173524
8.3%
b 2173524
8.3%
5 2173524
8.3%
0 1449016
 
5.6%
f 1449016
 
5.6%
6 1449016
 
5.6%
8 1449016
 
5.6%
a 1449016
 
5.6%
Other values (7) 5071556
19.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26082288
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 4347048
16.7%
- 2898032
11.1%
2 2173524
8.3%
b 2173524
8.3%
5 2173524
8.3%
0 1449016
 
5.6%
f 1449016
 
5.6%
6 1449016
 
5.6%
8 1449016
 
5.6%
a 1449016
 
5.6%
Other values (7) 5071556
19.4%

publishingCountry
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:56.252247image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1449016
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS
ValueCountFrequency (%)
us 724508
100.0%
2025-01-07T11:05:56.340164image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 724508
50.0%
S 724508
50.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1449016
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 724508
50.0%
S 724508
50.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1449016
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 724508
50.0%
S 724508
50.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1449016
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 724508
50.0%
S 724508
50.0%
Distinct37858
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:56.443171image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99520778
Min length20

Characters and Unicode

Total characters17384720
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique984 ?
Unique (%)0.1%

Sample

1st row2024-12-02T10:16:26.190Z
2nd row2024-12-02T10:16:26.321Z
3rd row2024-12-02T10:16:26.322Z
4th row2024-12-02T10:16:26.322Z
5th row2024-12-02T10:16:26.323Z
ValueCountFrequency (%)
2024-12-02t10:17:03.880z 100
 
< 0.1%
2024-12-02t10:17:08.512z 92
 
< 0.1%
2024-12-02t10:17:04.870z 87
 
< 0.1%
2024-12-02t10:17:05.654z 87
 
< 0.1%
2024-12-02t10:17:07.114z 85
 
< 0.1%
2024-12-02t10:16:59.768z 85
 
< 0.1%
2024-12-02t10:16:52.136z 85
 
< 0.1%
2024-12-02t10:16:58.778z 84
 
< 0.1%
2024-12-02t10:17:03.172z 84
 
< 0.1%
2024-12-02t10:17:07.495z 83
 
< 0.1%
Other values (37848) 723636
99.9%
2025-01-07T11:05:56.624425image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3187397
18.3%
0 2663851
15.3%
1 2462647
14.2%
: 1449016
8.3%
- 1449016
8.3%
4 1185381
 
6.8%
6 810755
 
4.7%
T 724508
 
4.2%
Z 724508
 
4.2%
. 723640
 
4.2%
Other values (5) 2004001
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17384720
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 3187397
18.3%
0 2663851
15.3%
1 2462647
14.2%
: 1449016
8.3%
- 1449016
8.3%
4 1185381
 
6.8%
6 810755
 
4.7%
T 724508
 
4.2%
Z 724508
 
4.2%
. 723640
 
4.2%
Other values (5) 2004001
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17384720
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 3187397
18.3%
0 2663851
15.3%
1 2462647
14.2%
: 1449016
8.3%
- 1449016
8.3%
4 1185381
 
6.8%
6 810755
 
4.7%
T 724508
 
4.2%
Z 724508
 
4.2%
. 723640
 
4.2%
Other values (5) 2004001
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17384720
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 3187397
18.3%
0 2663851
15.3%
1 2462647
14.2%
: 1449016
8.3%
- 1449016
8.3%
4 1185381
 
6.8%
6 810755
 
4.7%
T 724508
 
4.2%
Z 724508
 
4.2%
. 723640
 
4.2%
Other values (5) 2004001
11.5%

elevation
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

elevationAccuracy
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

depth
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

depthAccuracy
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

distanceFromCentroidInMeters
Real number (ℝ)

Missing 

Distinct149
Distinct (%)23.1%
Missing723864
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean2256.841767
Minimum0
Maximum4992.37105
Zeros6
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:56.699830image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile857.2535536
Q1857.2535536
median2818.630536
Q32818.630536
95-th percentile4618.527309
Maximum4992.37105
Range4992.37105
Interquartile range (IQR)1961.376982

Descriptive statistics

Standard deviation1312.822223
Coefficient of variation (CV)0.5817076951
Kurtosis-1.028590401
Mean2256.841767
Median Absolute Deviation (MAD)1402.236206
Skewness0.30591539
Sum1453406.098
Variance1723502.188
MonotonicityNot monotonic
2025-01-07T11:05:56.832324image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
857.2535536 226
 
< 0.1%
2818.630536 202
 
< 0.1%
4618.527309 27
 
< 0.1%
3800.284004 12
 
< 0.1%
1824.519626 10
 
< 0.1%
0 6
 
< 0.1%
1543.140798 6
 
< 0.1%
4852.601363 5
 
< 0.1%
3114.471841 4
 
< 0.1%
3029.93085 3
 
< 0.1%
Other values (139) 143
 
< 0.1%
(Missing) 723864
99.9%
ValueCountFrequency (%)
0 6
< 0.1%
253.452652 1
 
< 0.1%
533.2556305 1
 
< 0.1%
599.6747027 1
 
< 0.1%
605.9334686 1
 
< 0.1%
ValueCountFrequency (%)
4992.37105 1
< 0.1%
4985.80659 1
< 0.1%
4984.258263 1
< 0.1%
4978.129443 1
< 0.1%
4968.052222 1
< 0.1%

issue
Text

Distinct154
Distinct (%)< 0.1%
Missing193
Missing (%)< 0.1%
Memory size5.5 MiB
2025-01-07T11:05:56.887587image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length186
Median length181
Mean length68.38031105
Min length17

Characters and Unicode

Total characters49528885
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)< 0.1%

Sample

1st rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;GEODETIC_DATUM_ASSUMED_WGS84;TAXON_MATCH_NONE
2nd rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
3rd rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
4th rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;CONTINENT_DERIVED_FROM_COUNTRY
5th rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
ValueCountFrequency (%)
occurrence_status_inferred_from_individual_count 288609
39.8%
occurrence_status_inferred_from_individual_count;taxon_match_higherrank 165166
22.8%
occurrence_status_inferred_from_individual_count;taxon_match_none 89011
 
12.3%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;taxon_match_none 34505
 
4.8%
occurrence_status_inferred_from_individual_count;continent_derived_from_country 25422
 
3.5%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;continent_coordinate_mismatch;taxon_match_none 15005
 
2.1%
occurrence_status_inferred_from_individual_count;recorded_date_mismatch 12501
 
1.7%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;geodetic_datum_invalid;taxon_match_none 11612
 
1.6%
occurrence_status_inferred_from_individual_count;taxon_match_fuzzy 10754
 
1.5%
occurrence_status_inferred_from_individual_count;continent_derived_from_country;taxon_match_higherrank 10043
 
1.4%
Other values (144) 61687
 
8.5%
2025-01-07T11:05:57.022078image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 5044685
10.2%
R 4292364
 
8.7%
N 4233244
 
8.5%
E 3964433
 
8.0%
C 3659582
 
7.4%
I 3552475
 
7.2%
T 3530938
 
7.1%
U 3207403
 
6.5%
O 3183427
 
6.4%
D 2832439
 
5.7%
Other values (18) 12027895
24.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 49528885
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
_ 5044685
10.2%
R 4292364
 
8.7%
N 4233244
 
8.5%
E 3964433
 
8.0%
C 3659582
 
7.4%
I 3552475
 
7.2%
T 3530938
 
7.1%
U 3207403
 
6.5%
O 3183427
 
6.4%
D 2832439
 
5.7%
Other values (18) 12027895
24.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 49528885
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
_ 5044685
10.2%
R 4292364
 
8.7%
N 4233244
 
8.5%
E 3964433
 
8.0%
C 3659582
 
7.4%
I 3552475
 
7.2%
T 3530938
 
7.1%
U 3207403
 
6.5%
O 3183427
 
6.4%
D 2832439
 
5.7%
Other values (18) 12027895
24.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 49528885
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
_ 5044685
10.2%
R 4292364
 
8.7%
N 4233244
 
8.5%
E 3964433
 
8.0%
C 3659582
 
7.4%
I 3552475
 
7.2%
T 3530938
 
7.1%
U 3207403
 
6.5%
O 3183427
 
6.4%
D 2832439
 
5.7%
Other values (18) 12027895
24.3%

mediaType
Text

Missing 

Distinct58
Distinct (%)0.1%
Missing637882
Missing (%)88.0%
Memory size5.5 MiB
2025-01-07T11:05:57.080205image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1110
Median length1099
Mean length20.60165539
Min length10

Characters and Unicode

Total characters1784639
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)< 0.1%

Sample

1st rowStillImage
2nd rowStillImage
3rd rowStillImage
4th rowStillImage
5th rowStillImage;StillImage
ValueCountFrequency (%)
stillimage 36835
42.5%
stillimage;stillimage 35396
40.9%
stillimage;stillimage;stillimage;stillimage 5461
 
6.3%
stillimage;stillimage;stillimage 5225
 
6.0%
stillimage;stillimage;stillimage;stillimage;stillimage 2625
 
3.0%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 354
 
0.4%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 145
 
0.2%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 132
 
0.2%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 79
 
0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 74
 
0.1%
Other values (48) 300
 
0.3%
2025-01-07T11:05:57.212603image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 340230
19.1%
S 170115
9.5%
t 170115
9.5%
i 170115
9.5%
I 170115
9.5%
m 170115
9.5%
a 170115
9.5%
g 170115
9.5%
e 170115
9.5%
; 83489
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1784639
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 340230
19.1%
S 170115
9.5%
t 170115
9.5%
i 170115
9.5%
I 170115
9.5%
m 170115
9.5%
a 170115
9.5%
g 170115
9.5%
e 170115
9.5%
; 83489
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1784639
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 340230
19.1%
S 170115
9.5%
t 170115
9.5%
i 170115
9.5%
I 170115
9.5%
m 170115
9.5%
a 170115
9.5%
g 170115
9.5%
e 170115
9.5%
; 83489
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1784639
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 340230
19.1%
S 170115
9.5%
t 170115
9.5%
i 170115
9.5%
I 170115
9.5%
m 170115
9.5%
a 170115
9.5%
g 170115
9.5%
e 170115
9.5%
; 83489
 
4.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size707.7 KiB
False
620570 
True
103938 
ValueCountFrequency (%)
False 620570
85.7%
True 103938
 
14.3%
2025-01-07T11:05:57.277219image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

hasGeospatialIssues
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size707.7 KiB
False
723170 
True
 
1338
ValueCountFrequency (%)
False 723170
99.8%
True 1338
 
0.2%
2025-01-07T11:05:57.320401image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

taxonKey
Real number (ℝ)

Zeros 

Distinct65365
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4156268.397
Minimum0
Maximum12387090
Zeros171789
Zeros (%)23.7%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:57.372403image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median4806932
Q37794651
95-th percentile9255998
Maximum12387090
Range12387090
Interquartile range (IQR)7794645

Descriptive statistics

Standard deviation3563951.427
Coefficient of variation (CV)0.857488277
Kurtosis-1.280507827
Mean4156268.397
Median Absolute Deviation (MAD)3776216.5
Skewness0.1911040766
Sum3.011249704 × 1012
Variance1.270174977 × 1013
MonotonicityNot monotonic
2025-01-07T11:05:57.438421image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 171789
 
23.7%
216 16872
 
2.3%
8513230 13693
 
1.9%
4806028 12281
 
1.7%
6 11457
 
1.6%
359 4656
 
0.6%
44 4268
 
0.6%
729 3674
 
0.5%
353 3566
 
0.5%
2481460 3232
 
0.4%
Other values (65355) 479020
66.1%
ValueCountFrequency (%)
0 171789
23.7%
1 1114
 
0.2%
6 11457
 
1.6%
42 952
 
0.1%
43 51
 
< 0.1%
ValueCountFrequency (%)
12387090 1
 
< 0.1%
12385426 4
< 0.1%
12385220 2
 
< 0.1%
12383973 1
 
< 0.1%
12379591 6
< 0.1%

acceptedTaxonKey
Real number (ℝ)

Missing 

Distinct58335
Distinct (%)10.6%
Missing171789
Missing (%)23.7%
Infinite0
Infinite (%)0.0%
Mean5515085.25
Minimum1
Maximum12385426
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:57.504280image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile216
Q13249393
median4941659
Q38513230
95-th percentile9626241
Maximum12385426
Range12385425
Interquartile range (IQR)5263837

Descriptive statistics

Standard deviation3184869.125
Coefficient of variation (CV)0.5774832084
Kurtosis-0.8885403732
Mean5515085.25
Median Absolute Deviation (MAD)2688948
Skewness-0.1769613565
Sum3.048292404 × 1012
Variance1.014339134 × 1013
MonotonicityNot monotonic
2025-01-07T11:05:57.570790image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
216 16872
 
2.3%
8513230 13693
 
1.9%
4806028 12281
 
1.7%
6 11457
 
1.6%
359 4656
 
0.6%
44 4268
 
0.6%
729 3674
 
0.5%
353 3566
 
0.5%
2481460 3232
 
0.4%
4832444 3022
 
0.4%
Other values (58325) 475998
65.7%
(Missing) 171789
 
23.7%
ValueCountFrequency (%)
1 1114
 
0.2%
6 11457
1.6%
42 952
 
0.1%
43 51
 
< 0.1%
44 4268
 
0.6%
ValueCountFrequency (%)
12385426 4
 
< 0.1%
12385220 2
 
< 0.1%
12379591 6
 
< 0.1%
12362277 15
< 0.1%
12358726 5
 
< 0.1%

kingdomKey
Real number (ℝ)

Zeros 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.303661243
Minimum0
Maximum7
Zeros171929
Zeros (%)23.7%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:57.625153image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.508442348
Coefficient of variation (CV)1.157081531
Kurtosis2.902387583
Mean1.303661243
Median Absolute Deviation (MAD)0
Skewness1.923133372
Sum944513
Variance2.275398317
MonotonicityNot monotonic
2025-01-07T11:05:57.672151image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 446288
61.6%
0 171929
 
23.7%
4 69124
 
9.5%
6 36324
 
5.0%
3 502
 
0.1%
7 287
 
< 0.1%
5 54
 
< 0.1%
ValueCountFrequency (%)
0 171929
 
23.7%
1 446288
61.6%
3 502
 
0.1%
4 69124
 
9.5%
5 54
 
< 0.1%
ValueCountFrequency (%)
7 287
 
< 0.1%
6 36324
5.0%
5 54
 
< 0.1%
4 69124
9.5%
3 502
 
0.1%

phylumKey
Real number (ℝ)

Missing 

Distinct40
Distinct (%)< 0.1%
Missing192842
Missing (%)26.6%
Infinite0
Infinite (%)0.0%
Mean1373510.734
Minimum9
Maximum12228025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:57.729055image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile44
Q144
median53
Q3110
95-th percentile8376456
Maximum12228025
Range12228016
Interquartile range (IQR)66

Descriptive statistics

Standard deviation3060656.412
Coefficient of variation (CV)2.228345463
Kurtosis1.208523107
Mean1373510.734
Median Absolute Deviation (MAD)9
Skewness1.786678435
Sum7.302489577 × 1011
Variance9.367617675 × 1012
MonotonicityNot monotonic
2025-01-07T11:05:57.792248image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
44 148527
20.5%
54 101505
14.0%
52 66708
 
9.2%
8376456 66099
 
9.1%
110 65633
 
9.1%
50 27100
 
3.7%
7707728 21340
 
2.9%
53 13677
 
1.9%
43 6914
 
1.0%
42 3027
 
0.4%
Other values (30) 11136
 
1.5%
(Missing) 192842
26.6%
ValueCountFrequency (%)
9 20
 
< 0.1%
14 46
 
< 0.1%
32 1
 
< 0.1%
33 225
< 0.1%
35 20
 
< 0.1%
ValueCountFrequency (%)
12228025 12
 
< 0.1%
9778081 1
 
< 0.1%
8770992 11
 
< 0.1%
8376456 66099
9.1%
8173593 15
 
< 0.1%

classKey
Real number (ℝ)

Missing 

Distinct92
Distinct (%)< 0.1%
Missing272566
Missing (%)37.6%
Infinite0
Infinite (%)0.0%
Mean1466432.75
Minimum116
Maximum12259753
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:57.856752image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum116
5-th percentile121
Q1210
median220
Q3359
95-th percentile9273948
Maximum12259753
Range12259637
Interquartile range (IQR)149

Descriptive statistics

Standard deviation3184973.092
Coefficient of variation (CV)2.17191896
Kurtosis1.344083486
Mean1466432.75
Median Absolute Deviation (MAD)83
Skewness1.775836497
Sum6.627425498 × 1011
Variance1.01440536 × 1013
MonotonicityNot monotonic
2025-01-07T11:05:57.925243image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
359 59795
 
8.3%
7434778 42882
 
5.9%
210 39551
 
5.5%
212 34584
 
4.8%
216 32733
 
4.5%
225 24245
 
3.3%
353 23481
 
3.2%
121 23303
 
3.2%
9273948 22315
 
3.1%
137 22257
 
3.1%
Other values (82) 126796
17.5%
(Missing) 272566
37.6%
ValueCountFrequency (%)
116 36
 
< 0.1%
120 659
 
0.1%
121 23303
3.2%
125 9
 
< 0.1%
126 11
 
< 0.1%
ValueCountFrequency (%)
12259753 1
 
< 0.1%
12203163 1
 
< 0.1%
12186859 12
 
< 0.1%
11733052 62
 
< 0.1%
11592253 1006
0.1%

orderKey
Real number (ℝ)

Missing 

Distinct484
Distinct (%)0.1%
Missing369296
Missing (%)51.0%
Infinite0
Infinite (%)0.0%
Mean3512590.676
Minimum370
Maximum12263124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:57.987390image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum370
5-th percentile509
Q1798
median1436
Q37692889
95-th percentile11151631
Maximum12263124
Range12262754
Interquartile range (IQR)7692091

Descriptive statistics

Standard deviation4380254.677
Coefficient of variation (CV)1.247015403
Kurtosis-1.502677218
Mean3512590.676
Median Absolute Deviation (MAD)799
Skewness0.5410560688
Sum1.247714359 × 1012
Variance1.918663103 × 1013
MonotonicityNot monotonic
2025-01-07T11:05:58.054899image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7692889 32460
 
4.5%
811 14185
 
2.0%
1419 14086
 
1.9%
1438 12424
 
1.7%
885 11376
 
1.6%
733 10382
 
1.4%
7192755 9895
 
1.4%
731 8981
 
1.2%
509 8715
 
1.2%
795 7870
 
1.1%
Other values (474) 224838
31.0%
(Missing) 369296
51.0%
ValueCountFrequency (%)
370 300
 
< 0.1%
371 3664
0.5%
376 8
 
< 0.1%
381 5
 
< 0.1%
392 635
 
0.1%
ValueCountFrequency (%)
12263124 1
 
< 0.1%
12261528 2195
0.3%
12260364 11
 
< 0.1%
12244639 2
 
< 0.1%
12243044 2
 
< 0.1%

familyKey
Real number (ℝ)

Missing 

Distinct4832
Distinct (%)1.0%
Missing258765
Missing (%)35.7%
Infinite0
Infinite (%)0.0%
Mean3036480.23
Minimum1895
Maximum12262968
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:58.119800image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1895
5-th percentile2918
Q17086
median3252093
Q34834682
95-th percentile8052057
Maximum12262968
Range12261073
Interquartile range (IQR)4827596

Descriptive statistics

Standard deviation2821037.453
Coefficient of variation (CV)0.9290485166
Kurtosis-0.5522487965
Mean3036480.23
Median Absolute Deviation (MAD)3242579
Skewness0.508338039
Sum1.414219412 × 1012
Variance7.958252313 × 1012
MonotonicityNot monotonic
2025-01-07T11:05:58.257545image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3255384 14086
 
1.9%
9496 13693
 
1.9%
9339 9409
 
1.3%
5888 7013
 
1.0%
2211 5646
 
0.8%
2986 5251
 
0.7%
5310 4763
 
0.7%
7923659 3864
 
0.5%
5479 3840
 
0.5%
5446 3794
 
0.5%
Other values (4822) 394384
54.4%
(Missing) 258765
35.7%
ValueCountFrequency (%)
1895 12
< 0.1%
1897 3
 
< 0.1%
1978 20
< 0.1%
1989 12
< 0.1%
2006 29
< 0.1%
ValueCountFrequency (%)
12262968 4
 
< 0.1%
12247189 9
 
< 0.1%
12246268 3
 
< 0.1%
12236981 32
< 0.1%
12234980 3
 
< 0.1%

genusKey
Real number (ℝ)

Missing 

Distinct20311
Distinct (%)4.2%
Missing245070
Missing (%)33.8%
Infinite0
Infinite (%)0.0%
Mean4935876.249
Minimum1000424
Maximum12385426
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:58.316289image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1000424
5-th percentile2278992
Q13251308
median4830391
Q34897257
95-th percentile8513230
Maximum12385426
Range11385002
Interquartile range (IQR)1645949

Descriptive statistics

Standard deviation2083699.037
Coefficient of variation (CV)0.4221538248
Kurtosis0.07746136144
Mean4935876.249
Median Absolute Deviation (MAD)598535
Skewness0.610001942
Sum2.366446637 × 1012
Variance4.341801678 × 1012
MonotonicityNot monotonic
2025-01-07T11:05:58.380289image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8513230 13693
 
1.9%
4806028 12281
 
1.7%
2481443 6789
 
0.9%
4833150 3770
 
0.5%
4832444 3029
 
0.4%
2417963 2974
 
0.4%
4848792 2250
 
0.3%
4851051 2208
 
0.3%
4870176 2080
 
0.3%
2498190 2051
 
0.3%
Other values (20301) 428313
59.1%
(Missing) 245070
33.8%
ValueCountFrequency (%)
1000424 11
 
< 0.1%
1003585 4
 
< 0.1%
1003655 29
< 0.1%
1003657 2
 
< 0.1%
1003659 3
 
< 0.1%
ValueCountFrequency (%)
12385426 4
< 0.1%
12385220 2
 
< 0.1%
12384711 5
< 0.1%
12379591 6
< 0.1%
12378210 2
 
< 0.1%

subgenusKey
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

speciesKey
Real number (ℝ)

Missing 

Distinct45066
Distinct (%)16.4%
Missing450165
Missing (%)62.1%
Infinite0
Infinite (%)0.0%
Mean7340362.403
Minimum1003615
Maximum12353765
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 MiB
2025-01-07T11:05:58.446613image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1003615
5-th percentile2441022
Q14977965
median8423909
Q39037391.5
95-th percentile11127348
Maximum12353765
Range11350150
Interquartile range (IQR)4059426.5

Descriptive statistics

Standard deviation2477246.806
Coefficient of variation (CV)0.3374829021
Kurtosis-0.4744667152
Mean7340362.403
Median Absolute Deviation (MAD)1034777
Skewness-0.5664310113
Sum2.013777043 × 1012
Variance6.136751738 × 1012
MonotonicityNot monotonic
2025-01-07T11:05:58.510436image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2481460 3232
 
0.4%
2481469 1833
 
0.3%
9413495 1648
 
0.2%
8819428 1401
 
0.2%
4941659 1115
 
0.2%
2481465 1050
 
0.1%
5816525 1044
 
0.1%
5816410 917
 
0.1%
4874907 816
 
0.1%
12198857 814
 
0.1%
Other values (45056) 260473
36.0%
(Missing) 450165
62.1%
ValueCountFrequency (%)
1003615 2
< 0.1%
1003627 2
< 0.1%
1003667 1
< 0.1%
1003733 1
< 0.1%
1003829 1
< 0.1%
ValueCountFrequency (%)
12353765 1
 
< 0.1%
12326275 2
< 0.1%
12279081 4
< 0.1%
12266515 1
 
< 0.1%
12266463 2
< 0.1%

species
Text

Missing 

Distinct45045
Distinct (%)16.4%
Missing450165
Missing (%)62.1%
Memory size5.5 MiB
2025-01-07T11:05:58.700557image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length36
Mean length19.97971153
Min length9

Characters and Unicode

Total characters5481294
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16582 ?
Unique (%)6.0%

Sample

1st rowDamaliscus lunatus
2nd rowAcrochordiceras hyatti
3rd rowAsterocyclina minima
4th rowCarcharias tricuspidatus
5th rowEnteletes rotundobesus
ValueCountFrequency (%)
pterodroma 6569
 
1.2%
phaeopygia 3232
 
0.6%
carcharias 2554
 
0.5%
hustedia 2069
 
0.4%
alba 2031
 
0.4%
oxyrhina 1714
 
0.3%
lepidocyclina 1710
 
0.3%
hyopsodus 1699
 
0.3%
megalodon 1650
 
0.3%
bolivina 1496
 
0.3%
Other values (34798) 523962
95.5%
2025-01-07T11:05:58.970377image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 606832
 
11.1%
i 523413
 
9.5%
s 407795
 
7.4%
e 395509
 
7.2%
o 376936
 
6.9%
r 355606
 
6.5%
n 311565
 
5.7%
l 303075
 
5.5%
274343
 
5.0%
t 273072
 
5.0%
Other values (44) 1653148
30.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5481294
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 606832
 
11.1%
i 523413
 
9.5%
s 407795
 
7.4%
e 395509
 
7.2%
o 376936
 
6.9%
r 355606
 
6.5%
n 311565
 
5.7%
l 303075
 
5.5%
274343
 
5.0%
t 273072
 
5.0%
Other values (44) 1653148
30.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5481294
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 606832
 
11.1%
i 523413
 
9.5%
s 407795
 
7.4%
e 395509
 
7.2%
o 376936
 
6.9%
r 355606
 
6.5%
n 311565
 
5.7%
l 303075
 
5.5%
274343
 
5.0%
t 273072
 
5.0%
Other values (44) 1653148
30.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5481294
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 606832
 
11.1%
i 523413
 
9.5%
s 407795
 
7.4%
e 395509
 
7.2%
o 376936
 
6.9%
r 355606
 
6.5%
n 311565
 
5.7%
l 303075
 
5.5%
274343
 
5.0%
t 273072
 
5.0%
Other values (44) 1653148
30.2%
Distinct58335
Distinct (%)10.6%
Missing171789
Missing (%)23.7%
Memory size5.5 MiB
2025-01-07T11:05:59.172994image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length124
Median length80
Mean length28.18863111
Min length4

Characters and Unicode

Total characters15580392
Distinct characters109
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20407 ?
Unique (%)3.7%

Sample

1st rowDamaliscus lunatus (Burchell, 1823)
2nd rowAcrochordiceras hyatti Meek, 1877
3rd rowAsterocyclina minima (Cushman, 1918)
4th rowCarcharias tricuspidatus Day, 1878
5th rowEnteletes rotundobesus Cooper & Grant, 1976
ValueCountFrequency (%)
80122
 
4.1%
walcott 31024
 
1.6%
cooper 23991
 
1.2%
insecta 16885
 
0.9%
1912 16538
 
0.8%
cushman 16371
 
0.8%
grant 16172
 
0.8%
1976 14710
 
0.7%
genus 13850
 
0.7%
b 13693
 
0.7%
Other values (46962) 1721141
87.6%
2025-01-07T11:05:59.454148image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1411778
 
9.1%
a 1238433
 
7.9%
e 968772
 
6.2%
i 903533
 
5.8%
o 818690
 
5.3%
r 805467
 
5.2%
s 768080
 
4.9%
n 717605
 
4.6%
l 693504
 
4.5%
t 605528
 
3.9%
Other values (99) 6649002
42.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15580392
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1411778
 
9.1%
a 1238433
 
7.9%
e 968772
 
6.2%
i 903533
 
5.8%
o 818690
 
5.3%
r 805467
 
5.2%
s 768080
 
4.9%
n 717605
 
4.6%
l 693504
 
4.5%
t 605528
 
3.9%
Other values (99) 6649002
42.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15580392
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1411778
 
9.1%
a 1238433
 
7.9%
e 968772
 
6.2%
i 903533
 
5.8%
o 818690
 
5.3%
r 805467
 
5.2%
s 768080
 
4.9%
n 717605
 
4.6%
l 693504
 
4.5%
t 605528
 
3.9%
Other values (99) 6649002
42.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15580392
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1411778
 
9.1%
a 1238433
 
7.9%
e 968772
 
6.2%
i 903533
 
5.8%
o 818690
 
5.3%
r 805467
 
5.2%
s 768080
 
4.9%
n 717605
 
4.6%
l 693504
 
4.5%
t 605528
 
3.9%
Other values (99) 6649002
42.7%
Distinct97401
Distinct (%)17.6%
Missing171332
Missing (%)23.6%
Memory size5.5 MiB
2025-01-07T11:05:59.662979image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length62
Median length56
Mean length18.07695742
Min length5

Characters and Unicode

Total characters9999739
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44766 ?
Unique (%)8.1%

Sample

1st rowDamaliscus lunatus
2nd rowAcrochordiceras hyatti
3rd rowDiscocyclina (Asterocyclina) sculpturata
4th rowOdontaspis cuspidata
5th rowEnteletes rotundobesus
ValueCountFrequency (%)
sp 136960
 
12.1%
genus 56232
 
5.0%
insecta 16851
 
1.5%
splendens 12400
 
1.1%
marrella 12281
 
1.1%
pterodroma 7305
 
0.6%
var 6498
 
0.6%
callophoca 3770
 
0.3%
isurus 3463
 
0.3%
ostracoda 3391
 
0.3%
Other values (53913) 873954
77.1%
2025-01-07T11:05:59.941735image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1021294
 
10.2%
s 909134
 
9.1%
i 819278
 
8.2%
e 762530
 
7.6%
o 610330
 
6.1%
r 609311
 
6.1%
n 592254
 
5.9%
579929
 
5.8%
l 537519
 
5.4%
u 466436
 
4.7%
Other values (62) 3091724
30.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9999739
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1021294
 
10.2%
s 909134
 
9.1%
i 819278
 
8.2%
e 762530
 
7.6%
o 610330
 
6.1%
r 609311
 
6.1%
n 592254
 
5.9%
579929
 
5.8%
l 537519
 
5.4%
u 466436
 
4.7%
Other values (62) 3091724
30.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9999739
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1021294
 
10.2%
s 909134
 
9.1%
i 819278
 
8.2%
e 762530
 
7.6%
o 610330
 
6.1%
r 609311
 
6.1%
n 592254
 
5.9%
579929
 
5.8%
l 537519
 
5.4%
u 466436
 
4.7%
Other values (62) 3091724
30.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9999739
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1021294
 
10.2%
s 909134
 
9.1%
i 819278
 
8.2%
e 762530
 
7.6%
o 610330
 
6.1%
r 609311
 
6.1%
n 592254
 
5.9%
579929
 
5.8%
l 537519
 
5.4%
u 466436
 
4.7%
Other values (62) 3091724
30.9%

typifiedName
Text

Constant  Missing 

Distinct1
Distinct (%)14.3%
Missing724501
Missing (%)> 99.9%
Memory size5.5 MiB
2025-01-07T11:05:59.995276image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters28
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowType
2nd rowType
3rd rowType
4th rowType
5th rowType
ValueCountFrequency (%)
type 7
100.0%
2025-01-07T11:06:00.086256image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 7
25.0%
y 7
25.0%
p 7
25.0%
e 7
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 28
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
T 7
25.0%
y 7
25.0%
p 7
25.0%
e 7
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 28
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
T 7
25.0%
y 7
25.0%
p 7
25.0%
e 7
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 28
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
T 7
25.0%
y 7
25.0%
p 7
25.0%
e 7
25.0%

protocol
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:06:00.127796image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters2173524
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEML
2nd rowEML
3rd rowEML
4th rowEML
5th rowEML
ValueCountFrequency (%)
eml 724508
100.0%
2025-01-07T11:06:00.219845image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 724508
33.3%
M 724508
33.3%
L 724508
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2173524
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 724508
33.3%
M 724508
33.3%
L 724508
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2173524
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 724508
33.3%
M 724508
33.3%
L 724508
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2173524
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 724508
33.3%
M 724508
33.3%
L 724508
33.3%
Distinct37858
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:06:00.324096image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99520778
Min length20

Characters and Unicode

Total characters17384720
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique984 ?
Unique (%)0.1%

Sample

1st row2024-12-02T10:16:26.190Z
2nd row2024-12-02T10:16:26.321Z
3rd row2024-12-02T10:16:26.322Z
4th row2024-12-02T10:16:26.322Z
5th row2024-12-02T10:16:26.323Z
ValueCountFrequency (%)
2024-12-02t10:17:03.880z 100
 
< 0.1%
2024-12-02t10:17:08.512z 92
 
< 0.1%
2024-12-02t10:17:04.870z 87
 
< 0.1%
2024-12-02t10:17:05.654z 87
 
< 0.1%
2024-12-02t10:17:07.114z 85
 
< 0.1%
2024-12-02t10:16:59.768z 85
 
< 0.1%
2024-12-02t10:16:52.136z 85
 
< 0.1%
2024-12-02t10:16:58.778z 84
 
< 0.1%
2024-12-02t10:17:03.172z 84
 
< 0.1%
2024-12-02t10:17:07.495z 83
 
< 0.1%
Other values (37848) 723636
99.9%
2025-01-07T11:06:00.509873image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3187397
18.3%
0 2663851
15.3%
1 2462647
14.2%
: 1449016
8.3%
- 1449016
8.3%
4 1185381
 
6.8%
6 810755
 
4.7%
T 724508
 
4.2%
Z 724508
 
4.2%
. 723640
 
4.2%
Other values (5) 2004001
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17384720
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 3187397
18.3%
0 2663851
15.3%
1 2462647
14.2%
: 1449016
8.3%
- 1449016
8.3%
4 1185381
 
6.8%
6 810755
 
4.7%
T 724508
 
4.2%
Z 724508
 
4.2%
. 723640
 
4.2%
Other values (5) 2004001
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17384720
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 3187397
18.3%
0 2663851
15.3%
1 2462647
14.2%
: 1449016
8.3%
- 1449016
8.3%
4 1185381
 
6.8%
6 810755
 
4.7%
T 724508
 
4.2%
Z 724508
 
4.2%
. 723640
 
4.2%
Other values (5) 2004001
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17384720
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 3187397
18.3%
0 2663851
15.3%
1 2462647
14.2%
: 1449016
8.3%
- 1449016
8.3%
4 1185381
 
6.8%
6 810755
 
4.7%
T 724508
 
4.2%
Z 724508
 
4.2%
. 723640
 
4.2%
Other values (5) 2004001
11.5%

lastCrawled
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:06:00.570875image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters17388192
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-12-02T10:02:33.848Z
2nd row2024-12-02T10:02:33.848Z
3rd row2024-12-02T10:02:33.848Z
4th row2024-12-02T10:02:33.848Z
5th row2024-12-02T10:02:33.848Z
ValueCountFrequency (%)
2024-12-02t10:02:33.848z 724508
100.0%
2025-01-07T11:06:00.678988image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3622540
20.8%
0 2898032
16.7%
4 1449016
 
8.3%
- 1449016
 
8.3%
1 1449016
 
8.3%
: 1449016
 
8.3%
3 1449016
 
8.3%
8 1449016
 
8.3%
T 724508
 
4.2%
. 724508
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17388192
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 3622540
20.8%
0 2898032
16.7%
4 1449016
 
8.3%
- 1449016
 
8.3%
1 1449016
 
8.3%
: 1449016
 
8.3%
3 1449016
 
8.3%
8 1449016
 
8.3%
T 724508
 
4.2%
. 724508
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17388192
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 3622540
20.8%
0 2898032
16.7%
4 1449016
 
8.3%
- 1449016
 
8.3%
1 1449016
 
8.3%
: 1449016
 
8.3%
3 1449016
 
8.3%
8 1449016
 
8.3%
T 724508
 
4.2%
. 724508
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17388192
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 3622540
20.8%
0 2898032
16.7%
4 1449016
 
8.3%
- 1449016
 
8.3%
1 1449016
 
8.3%
: 1449016
 
8.3%
3 1449016
 
8.3%
8 1449016
 
8.3%
T 724508
 
4.2%
. 724508
 
4.2%

repatriated
Boolean

Missing 

Distinct2
Distinct (%)< 0.1%
Missing158317
Missing (%)21.9%
Memory size5.5 MiB
False
428942 
True
137249 
(Missing)
158317 
ValueCountFrequency (%)
False 428942
59.2%
True 137249
 
18.9%
(Missing) 158317
 
21.9%
2025-01-07T11:06:00.735310image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

relativeOrganismQuantity
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

projectId
Unsupported

Missing  Rejected  Unsupported 

Missing724508
Missing (%)100.0%
Memory size5.5 MiB

isSequenced
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size707.7 KiB
False
724508 
ValueCountFrequency (%)
False 724508
100.0%
2025-01-07T11:06:00.777309image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

gbifRegion
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing160612
Missing (%)22.2%
Memory size5.5 MiB
2025-01-07T11:06:00.813652image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.4128545
Min length4

Characters and Unicode

Total characters6999559
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowAFRICA
3rd rowNORTH_AMERICA
4th rowLATIN_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 468544
83.1%
latin_america 47663
 
8.5%
europe 16154
 
2.9%
asia 10382
 
1.8%
oceania 9334
 
1.7%
africa 8278
 
1.5%
antarctica 3541
 
0.6%
2025-01-07T11:06:00.919000image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1146688
16.4%
R 1012724
14.5%
I 595405
8.5%
E 557849
8.0%
C 540901
7.7%
N 529082
7.6%
T 523289
7.5%
M 516207
7.4%
_ 516207
7.4%
O 494032
7.1%
Other values (6) 567175
8.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6999559
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 1146688
16.4%
R 1012724
14.5%
I 595405
8.5%
E 557849
8.0%
C 540901
7.7%
N 529082
7.6%
T 523289
7.5%
M 516207
7.4%
_ 516207
7.4%
O 494032
7.1%
Other values (6) 567175
8.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6999559
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 1146688
16.4%
R 1012724
14.5%
I 595405
8.5%
E 557849
8.0%
C 540901
7.7%
N 529082
7.6%
T 523289
7.5%
M 516207
7.4%
_ 516207
7.4%
O 494032
7.1%
Other values (6) 567175
8.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6999559
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 1146688
16.4%
R 1012724
14.5%
I 595405
8.5%
E 557849
8.0%
C 540901
7.7%
N 529082
7.6%
T 523289
7.5%
M 516207
7.4%
_ 516207
7.4%
O 494032
7.1%
Other values (6) 567175
8.1%

publishedByGbifRegion
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.5 MiB
2025-01-07T11:06:00.965998image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters9418604
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowNORTH_AMERICA
3rd rowNORTH_AMERICA
4th rowNORTH_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 724508
100.0%
2025-01-07T11:06:01.062875image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 1449016
15.4%
A 1449016
15.4%
N 724508
7.7%
O 724508
7.7%
T 724508
7.7%
H 724508
7.7%
_ 724508
7.7%
M 724508
7.7%
E 724508
7.7%
I 724508
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9418604
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
R 1449016
15.4%
A 1449016
15.4%
N 724508
7.7%
O 724508
7.7%
T 724508
7.7%
H 724508
7.7%
_ 724508
7.7%
M 724508
7.7%
E 724508
7.7%
I 724508
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9418604
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
R 1449016
15.4%
A 1449016
15.4%
N 724508
7.7%
O 724508
7.7%
T 724508
7.7%
H 724508
7.7%
_ 724508
7.7%
M 724508
7.7%
E 724508
7.7%
I 724508
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9418604
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
R 1449016
15.4%
A 1449016
15.4%
N 724508
7.7%
O 724508
7.7%
T 724508
7.7%
H 724508
7.7%
_ 724508
7.7%
M 724508
7.7%
E 724508
7.7%
I 724508
7.7%

level0Gid
Text

Missing 

Distinct88
Distinct (%)0.2%
Missing686240
Missing (%)94.7%
Memory size5.5 MiB
2025-01-07T11:06:01.141668image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters114804
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)< 0.1%

Sample

1st rowUSA
2nd rowUSA
3rd rowUSA
4th rowUSA
5th rowUSA
ValueCountFrequency (%)
usa 33578
87.7%
mex 743
 
1.9%
can 398
 
1.0%
gum 255
 
0.7%
mnp 228
 
0.6%
pan 217
 
0.6%
idn 210
 
0.5%
umi 206
 
0.5%
fra 198
 
0.5%
pak 155
 
0.4%
Other values (78) 2080
 
5.4%
2025-01-07T11:06:01.268511image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 35038
30.5%
U 34448
30.0%
S 33870
29.5%
M 1679
 
1.5%
N 1312
 
1.1%
E 1296
 
1.1%
P 945
 
0.8%
I 802
 
0.7%
X 743
 
0.6%
R 715
 
0.6%
Other values (15) 3956
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 114804
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 35038
30.5%
U 34448
30.0%
S 33870
29.5%
M 1679
 
1.5%
N 1312
 
1.1%
E 1296
 
1.1%
P 945
 
0.8%
I 802
 
0.7%
X 743
 
0.6%
R 715
 
0.6%
Other values (15) 3956
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 114804
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 35038
30.5%
U 34448
30.0%
S 33870
29.5%
M 1679
 
1.5%
N 1312
 
1.1%
E 1296
 
1.1%
P 945
 
0.8%
I 802
 
0.7%
X 743
 
0.6%
R 715
 
0.6%
Other values (15) 3956
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 114804
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 35038
30.5%
U 34448
30.0%
S 33870
29.5%
M 1679
 
1.5%
N 1312
 
1.1%
E 1296
 
1.1%
P 945
 
0.8%
I 802
 
0.7%
X 743
 
0.6%
R 715
 
0.6%
Other values (15) 3956
 
3.4%

level0Name
Text

Missing 

Distinct88
Distinct (%)0.2%
Missing686240
Missing (%)94.7%
Memory size5.5 MiB
2025-01-07T11:06:01.443984image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length13
Mean length12.50533082
Min length4

Characters and Unicode

Total characters478554
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)< 0.1%

Sample

1st rowUnited States
2nd rowUnited States
3rd rowUnited States
4th rowUnited States
5th rowUnited States
ValueCountFrequency (%)
united 33879
46.0%
states 33784
45.9%
méxico 743
 
1.0%
canada 398
 
0.5%
islands 291
 
0.4%
guam 255
 
0.3%
northern 235
 
0.3%
mariana 228
 
0.3%
panama 217
 
0.3%
indonesia 210
 
0.3%
Other values (93) 3333
 
4.5%
2025-01-07T11:06:01.600578image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 102628
21.4%
e 69101
14.4%
a 39466
 
8.2%
n 37290
 
7.8%
i 37192
 
7.8%
35305
 
7.4%
s 35286
 
7.4%
d 35157
 
7.3%
S 34062
 
7.1%
U 33936
 
7.1%
Other values (43) 19131
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 478554
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 102628
21.4%
e 69101
14.4%
a 39466
 
8.2%
n 37290
 
7.8%
i 37192
 
7.8%
35305
 
7.4%
s 35286
 
7.4%
d 35157
 
7.3%
S 34062
 
7.1%
U 33936
 
7.1%
Other values (43) 19131
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 478554
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 102628
21.4%
e 69101
14.4%
a 39466
 
8.2%
n 37290
 
7.8%
i 37192
 
7.8%
35305
 
7.4%
s 35286
 
7.4%
d 35157
 
7.3%
S 34062
 
7.1%
U 33936
 
7.1%
Other values (43) 19131
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 478554
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 102628
21.4%
e 69101
14.4%
a 39466
 
8.2%
n 37290
 
7.8%
i 37192
 
7.8%
35305
 
7.4%
s 35286
 
7.4%
d 35157
 
7.3%
S 34062
 
7.1%
U 33936
 
7.1%
Other values (43) 19131
 
4.0%

level1Gid
Text

Missing 

Distinct353
Distinct (%)0.9%
Missing686243
Missing (%)94.7%
Memory size5.5 MiB
2025-01-07T11:06:01.808100image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.803449628
Min length7

Characters and Unicode

Total characters298599
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)0.3%

Sample

1st rowUSA.10_1
2nd rowUSA.29_1
3rd rowUSA.2_1
4th rowUSA.44_1
5th rowUSA.38_1
ValueCountFrequency (%)
usa.44_1 3802
 
9.9%
usa.38_1 2959
 
7.7%
usa.23_1 2129
 
5.6%
usa.34_1 2095
 
5.5%
usa.10_1 1141
 
3.0%
usa.17_1 1123
 
2.9%
usa.32_1 1117
 
2.9%
usa.18_1 1042
 
2.7%
usa.1_1 1017
 
2.7%
usa.2_1 983
 
2.6%
Other values (343) 20857
54.5%
2025-01-07T11:06:02.072368image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 48709
16.3%
_ 38265
12.8%
. 38265
12.8%
A 35032
11.7%
U 34448
11.5%
S 33870
11.3%
4 15952
 
5.3%
3 14650
 
4.9%
2 8837
 
3.0%
8 5433
 
1.8%
Other values (27) 25138
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 298599
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 48709
16.3%
_ 38265
12.8%
. 38265
12.8%
A 35032
11.7%
U 34448
11.5%
S 33870
11.3%
4 15952
 
5.3%
3 14650
 
4.9%
2 8837
 
3.0%
8 5433
 
1.8%
Other values (27) 25138
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 298599
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 48709
16.3%
_ 38265
12.8%
. 38265
12.8%
A 35032
11.7%
U 34448
11.5%
S 33870
11.3%
4 15952
 
5.3%
3 14650
 
4.9%
2 8837
 
3.0%
8 5433
 
1.8%
Other values (27) 25138
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 298599
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 48709
16.3%
_ 38265
12.8%
. 38265
12.8%
A 35032
11.7%
U 34448
11.5%
S 33870
11.3%
4 15952
 
5.3%
3 14650
 
4.9%
2 8837
 
3.0%
8 5433
 
1.8%
Other values (27) 25138
8.4%

level1Name
Text

Missing 

Distinct353
Distinct (%)0.9%
Missing686243
Missing (%)94.7%
Memory size5.5 MiB
2025-01-07T11:06:02.271093image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length29
Mean length8.062981837
Min length3

Characters and Unicode

Total characters308530
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)0.3%

Sample

1st rowFlorida
2nd rowNevada
3rd rowAlaska
4th rowTexas
5th rowOregon
ValueCountFrequency (%)
texas 3802
 
8.4%
oregon 2959
 
6.5%
carolina 2734
 
6.0%
new 2376
 
5.2%
michigan 2129
 
4.7%
north 2102
 
4.6%
florida 1141
 
2.5%
kansas 1123
 
2.5%
mexico 1117
 
2.5%
kentucky 1042
 
2.3%
Other values (409) 24889
54.8%
2025-01-07T11:06:02.528723image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 41520
 
13.5%
i 26049
 
8.4%
o 23918
 
7.8%
n 23868
 
7.7%
e 19743
 
6.4%
r 18679
 
6.1%
s 17076
 
5.5%
l 13026
 
4.2%
h 9794
 
3.2%
t 9186
 
3.0%
Other values (71) 105671
34.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 308530
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 41520
 
13.5%
i 26049
 
8.4%
o 23918
 
7.8%
n 23868
 
7.7%
e 19743
 
6.4%
r 18679
 
6.1%
s 17076
 
5.5%
l 13026
 
4.2%
h 9794
 
3.2%
t 9186
 
3.0%
Other values (71) 105671
34.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 308530
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 41520
 
13.5%
i 26049
 
8.4%
o 23918
 
7.8%
n 23868
 
7.7%
e 19743
 
6.4%
r 18679
 
6.1%
s 17076
 
5.5%
l 13026
 
4.2%
h 9794
 
3.2%
t 9186
 
3.0%
Other values (71) 105671
34.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 308530
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 41520
 
13.5%
i 26049
 
8.4%
o 23918
 
7.8%
n 23868
 
7.7%
e 19743
 
6.4%
r 18679
 
6.1%
s 17076
 
5.5%
l 13026
 
4.2%
h 9794
 
3.2%
t 9186
 
3.0%
Other values (71) 105671
34.2%

level2Gid
Text

Missing 

Distinct1562
Distinct (%)4.2%
Missing687320
Missing (%)94.9%
Memory size5.5 MiB
2025-01-07T11:06:02.737472image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.68914704
Min length9

Characters and Unicode

Total characters397508
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique384 ?
Unique (%)1.0%

Sample

1st rowUSA.10.3_1
2nd rowUSA.29.10_1
3rd rowUSA.2.17_1
4th rowUSA.44.57_1
5th rowUSA.38.21_1
ValueCountFrequency (%)
usa.23.44_1 1758
 
4.7%
usa.38.21_1 1751
 
4.7%
mex.30.91_2 673
 
1.8%
usa.36.44_1 428
 
1.2%
usa.8.2_1 412
 
1.1%
usa.41.8_1 377
 
1.0%
usa.2.17_1 366
 
1.0%
usa.44.22_1 329
 
0.9%
usa.44.252_1 321
 
0.9%
usa.32.31_1 307
 
0.8%
Other values (1552) 30466
81.9%
2025-01-07T11:06:03.008127image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 74376
18.7%
1 61042
15.4%
_ 37188
9.4%
A 34984
8.8%
U 33973
8.5%
S 33842
8.5%
4 26872
 
6.8%
2 21885
 
5.5%
3 20338
 
5.1%
8 8756
 
2.2%
Other values (27) 44252
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 397508
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 74376
18.7%
1 61042
15.4%
_ 37188
9.4%
A 34984
8.8%
U 33973
8.5%
S 33842
8.5%
4 26872
 
6.8%
2 21885
 
5.5%
3 20338
 
5.1%
8 8756
 
2.2%
Other values (27) 44252
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 397508
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 74376
18.7%
1 61042
15.4%
_ 37188
9.4%
A 34984
8.8%
U 33973
8.5%
S 33842
8.5%
4 26872
 
6.8%
2 21885
 
5.5%
3 20338
 
5.1%
8 8756
 
2.2%
Other values (27) 44252
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 397508
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 74376
18.7%
1 61042
15.4%
_ 37188
9.4%
A 34984
8.8%
U 33973
8.5%
S 33842
8.5%
4 26872
 
6.8%
2 21885
 
5.5%
3 20338
 
5.1%
8 8756
 
2.2%
Other values (27) 44252
11.1%

level2Name
Text

Missing 

Distinct1254
Distinct (%)3.4%
Missing687320
Missing (%)94.9%
Memory size5.5 MiB
2025-01-07T11:06:03.242821image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length25
Mean length7.870119393
Min length3

Characters and Unicode

Total characters292674
Distinct characters85
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique303 ?
Unique (%)0.8%

Sample

1st rowBay
2nd rowLincoln
3rd rowNorth Slope
4th rowDallas
5th rowLincoln
ValueCountFrequency (%)
lake 3351
 
7.3%
hurron 1795
 
3.9%
lincoln 1776
 
3.9%
superior 694
 
1.5%
carranza 673
 
1.5%
jesús 673
 
1.5%
washington 612
 
1.3%
new 537
 
1.2%
san 534
 
1.2%
erie 465
 
1.0%
Other values (1364) 34807
75.8%
2025-01-07T11:06:03.539430image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 29477
 
10.1%
e 27848
 
9.5%
r 23544
 
8.0%
n 23216
 
7.9%
o 21878
 
7.5%
l 16497
 
5.6%
i 15387
 
5.3%
t 11258
 
3.8%
s 11244
 
3.8%
u 8940
 
3.1%
Other values (75) 103385
35.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 292674
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 29477
 
10.1%
e 27848
 
9.5%
r 23544
 
8.0%
n 23216
 
7.9%
o 21878
 
7.5%
l 16497
 
5.6%
i 15387
 
5.3%
t 11258
 
3.8%
s 11244
 
3.8%
u 8940
 
3.1%
Other values (75) 103385
35.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 292674
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 29477
 
10.1%
e 27848
 
9.5%
r 23544
 
8.0%
n 23216
 
7.9%
o 21878
 
7.5%
l 16497
 
5.6%
i 15387
 
5.3%
t 11258
 
3.8%
s 11244
 
3.8%
u 8940
 
3.1%
Other values (75) 103385
35.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 292674
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 29477
 
10.1%
e 27848
 
9.5%
r 23544
 
8.0%
n 23216
 
7.9%
o 21878
 
7.5%
l 16497
 
5.6%
i 15387
 
5.3%
t 11258
 
3.8%
s 11244
 
3.8%
u 8940
 
3.1%
Other values (75) 103385
35.3%

level3Gid
Text

Missing 

Distinct340
Distinct (%)17.0%
Missing722506
Missing (%)99.7%
Memory size5.5 MiB
2025-01-07T11:06:03.707646image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11.82917083
Min length11

Characters and Unicode

Total characters23682
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)7.9%

Sample

1st rowIDN.34.7.16_1
2nd rowMMR.7.4.6_1
3rd rowPOL.15.20.6_1
4th rowPAK.7.8.3_1
5th rowESP.17.1.4_1
ValueCountFrequency (%)
pan.4.2.2_1 216
 
10.8%
idn.34.7.16_1 162
 
8.1%
ecu.9.2.2_1 82
 
4.1%
can.9.24.1_1 79
 
3.9%
pak.7.8.3_1 59
 
2.9%
can.8.1.2_1 56
 
2.8%
mar.4.2.10_1 41
 
2.0%
can.9.22.1_1 37
 
1.8%
can.9.23.1_1 30
 
1.5%
can.9.32.5_1 30
 
1.5%
Other values (330) 1210
60.4%
2025-01-07T11:06:03.931283image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6006
25.4%
1 3975
16.8%
_ 2002
 
8.5%
2 1598
 
6.7%
A 1231
 
5.2%
4 921
 
3.9%
N 838
 
3.5%
3 797
 
3.4%
P 565
 
2.4%
C 518
 
2.2%
Other values (23) 5231
22.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23682
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 6006
25.4%
1 3975
16.8%
_ 2002
 
8.5%
2 1598
 
6.7%
A 1231
 
5.2%
4 921
 
3.9%
N 838
 
3.5%
3 797
 
3.4%
P 565
 
2.4%
C 518
 
2.2%
Other values (23) 5231
22.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23682
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 6006
25.4%
1 3975
16.8%
_ 2002
 
8.5%
2 1598
 
6.7%
A 1231
 
5.2%
4 921
 
3.9%
N 838
 
3.5%
3 797
 
3.4%
P 565
 
2.4%
C 518
 
2.2%
Other values (23) 5231
22.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23682
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 6006
25.4%
1 3975
16.8%
_ 2002
 
8.5%
2 1598
 
6.7%
A 1231
 
5.2%
4 921
 
3.9%
N 838
 
3.5%
3 797
 
3.4%
P 565
 
2.4%
C 518
 
2.2%
Other values (23) 5231
22.1%

level3Name
Text

Missing 

Distinct340
Distinct (%)17.0%
Missing722506
Missing (%)99.7%
Memory size5.5 MiB
2025-01-07T11:06:04.124598image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length24
Mean length11.58741259
Min length3

Characters and Unicode

Total characters23198
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)7.9%

Sample

1st rowSangkulirang
2nd rowThayet
3rd rowRaszków
4th rowMianwali
5th rown.a. (108)
ValueCountFrequency (%)
sur 216
 
6.2%
barrio 216
 
6.2%
lake 172
 
5.0%
sangkulirang 162
 
4.7%
santa 84
 
2.4%
n.a 82
 
2.4%
floreana 82
 
2.4%
mara 82
 
2.4%
cab 82
 
2.4%
isla 82
 
2.4%
Other values (426) 2205
63.6%
2025-01-07T11:06:04.378032image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3242
 
14.0%
r 2007
 
8.7%
n 1526
 
6.6%
i 1489
 
6.4%
1463
 
6.3%
e 1431
 
6.2%
o 1107
 
4.8%
u 917
 
4.0%
l 907
 
3.9%
S 747
 
3.2%
Other values (69) 8362
36.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23198
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3242
 
14.0%
r 2007
 
8.7%
n 1526
 
6.6%
i 1489
 
6.4%
1463
 
6.3%
e 1431
 
6.2%
o 1107
 
4.8%
u 917
 
4.0%
l 907
 
3.9%
S 747
 
3.2%
Other values (69) 8362
36.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23198
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3242
 
14.0%
r 2007
 
8.7%
n 1526
 
6.6%
i 1489
 
6.4%
1463
 
6.3%
e 1431
 
6.2%
o 1107
 
4.8%
u 917
 
4.0%
l 907
 
3.9%
S 747
 
3.2%
Other values (69) 8362
36.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23198
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3242
 
14.0%
r 2007
 
8.7%
n 1526
 
6.6%
i 1489
 
6.4%
1463
 
6.3%
e 1431
 
6.2%
o 1107
 
4.8%
u 917
 
4.0%
l 907
 
3.9%
S 747
 
3.2%
Other values (69) 8362
36.0%

iucnRedListCategory
Text

Missing 

Distinct9
Distinct (%)< 0.1%
Missing365809
Missing (%)50.5%
Memory size5.5 MiB
2025-01-07T11:06:04.441415image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters717398
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLC
2nd rowNE
3rd rowNE
4th rowNE
5th rowNE
ValueCountFrequency (%)
ne 340013
94.8%
lc 7458
 
2.1%
cr 3457
 
1.0%
vu 3162
 
0.9%
en 2012
 
0.6%
ex 1761
 
0.5%
nt 761
 
0.2%
dd 73
 
< 0.1%
ew 2
 
< 0.1%
2025-01-07T11:06:04.557064image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 343788
47.9%
N 342786
47.8%
C 10915
 
1.5%
L 7458
 
1.0%
R 3457
 
0.5%
V 3162
 
0.4%
U 3162
 
0.4%
X 1761
 
0.2%
T 761
 
0.1%
D 146
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 717398
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 343788
47.9%
N 342786
47.8%
C 10915
 
1.5%
L 7458
 
1.0%
R 3457
 
0.5%
V 3162
 
0.4%
U 3162
 
0.4%
X 1761
 
0.2%
T 761
 
0.1%
D 146
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 717398
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 343788
47.9%
N 342786
47.8%
C 10915
 
1.5%
L 7458
 
1.0%
R 3457
 
0.5%
V 3162
 
0.4%
U 3162
 
0.4%
X 1761
 
0.2%
T 761
 
0.1%
D 146
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 717398
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 343788
47.9%
N 342786
47.8%
C 10915
 
1.5%
L 7458
 
1.0%
R 3457
 
0.5%
V 3162
 
0.4%
U 3162
 
0.4%
X 1761
 
0.2%
T 761
 
0.1%
D 146
 
< 0.1%